(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/user-guide/ingest-data/for-observability/prometheus.md:301:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/user-guide/ingest-data/for-observability/prometheus.md:314: \"index.type\" = \"skipping\"\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/user-guide/deployments-administration/manage-data/compaction.md:22:![SST layout](/compaction-sst-file-layout.jpg)\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/user-guide/deployments-administration/manage-data/region-failover.md:50:

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

\nversioned_docs/version-1.0/reference/pipeline/pipeline-config.md:1002:- `skipping`: Specifies a column to use the skipping index type. The column must be of string type.\nversioned_docs/version-1.0/reference/pipeline/pipeline-config.md:1022:Specify which field uses the skipping index. This index speeds up the query on high cardinality fields but consumes far less storage for building index files. Refer to the [Transform Example](#transform-example) below for syntax.\nversioned_docs/version-1.0/reference/pipeline/pipeline-config.md:1059: index: skipping\nversioned_docs/version-1.0/reference/sql/information-schema/ssts-index-meta.md:2:keywords: [SST index metadata, Puffin index, inverted index, fulltext index, bloom filter, index metadata]\nversioned_docs/version-1.0/reference/sql/information-schema/ssts-index-meta.md:3:description: Provides access to SST (Sorted String Table) index metadata, including information about inverted indexes, fulltext indexes, and bloom filters stored in Puffin format.\nversioned_docs/version-1.0/reference/sql/information-schema/ssts-index-meta.md:8:The `SSTS_INDEX_META` table provides access to SST (Sorted String Table) index metadata collected from the manifest. This table surfaces information about Puffin index metadata, including inverted indexes, fulltext indexes, and bloom filters.\nversioned_docs/version-1.0/reference/sql/information-schema/ssts-index-meta.md:42:- `index_file_path`: The full path to the Puffin index file.\nversioned_docs/version-1.0/reference/sql/limit.md:61:`LIMIT n, m` allows to select the m rows from the result after skipping the first n rows. The `LIMIT m OFFSET n` syntax\nversioned_docs/version-1.0/reference/sql/offset.md:2:keywords: [SQL OFFSET clause, data retrieval, skipping rows]\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/reference/pipeline/pipeline-config.md:1018:- `skipping`: 用于指定某列使用 skipping 类型的索引（跳数索引），该列需要是字符串类型\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/reference/pipeline/pipeline-config.md:1039:通过 `index: skipping` 指定在哪个列上建立跳数索引，该索引只需少量存储空间的索引文件即可以加速在高基数列上的查询，写法请参考下方的 [Transform 示例](#transform-示例)。\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/reference/pipeline/pipeline-config.md:1076: index: skipping\nversioned_docs/version-1.0/reference/sql/alter.md:288:Enable skipping index on a column:\nversioned_docs/version-1.0/reference/sql/alter.md:294:The valid options for the skipping index include:\nversioned_docs/version-1.0/reference/sql/alter.md:314:Remove the skipping index:\nversioned_docs/version-1.0/reference/sql/alter.md:328:If the fulltext index has never been enabled, you can enable it and specify the `analyzer` and `case_sensitive` options. When the fulltext index is already enabled on a column, you can disable it but **cannot modify the options, and so does the skipping index**.\nversioned_docs/version-1.0/reference/sql/create.md:164:| `index.type` | Index type | **Only for metric engine** String value, supports `none`, `skipping`. |\nversioned_docs/version-1.0/reference/sql/create.md:315:#### Create a physical table with enable skipping index for columns\nversioned_docs/version-1.0/reference/sql/create.md:317:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-1.0/reference/sql/create.md:319:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-1.0/reference/sql/create.md:330: \"index.type\" = \"skipping\",\nversioned_docs/version-1.0/reference/sql/create.md:365:| SKIPPING INDEX | Creates a skipping index to speed up query on sparse data. |\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/reference/sql/information-schema/ssts-index-meta.md:2:keywords: [SST 索引元数据, Puffin 索引, 倒排索引, 全文索引, 布隆过滤器, 索引元数据]\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/reference/sql/information-schema/ssts-index-meta.md:3:description: 提供对 SST（排序字符串表）索引元数据的访问，包括以 Puffin 格式存储的倒排索引、全文索引和布隆过滤器的信息。\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/reference/sql/information-schema/ssts-index-meta.md:8:`SSTS_INDEX_META` 表提供对从清单中收集的 SST（排序字符串表）索引元数据的访问。该表显示 Puffin 索引元数据的信息，包括倒排索引、全文索引和布隆过滤器。\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/reference/sql/information-schema/ssts-index-meta.md:42:- `index_file_path`：Puffin 索引文件的完整路径。\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/reference/sql/create.md:164:| `index.type` | Index 类型 | **仅用于 metric engine** 字符串值，支持 `none`, `skipping`. |\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/reference/sql/create.md:321:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/reference/sql/create.md:334: \"index.type\" = \"skipping\",\nversioned_docs/version-1.0/getting-started/quick-start.md:106:For high-cardinality `trace_id`s, we have enabled the [skip index](/user-guide/manage-data/data-index.md#skipping-index).\nversioned_docs/version-1.0/contributor-guide/datanode/data-persistence-indexing.md:30:Apache Parquet file format provides inherent statistics in headers of column chunks and data pages, which are used for pruning and skipping.\nversioned_docs/version-1.0/contributor-guide/datanode/data-persistence-indexing.md:40:The index files utilize the [Puffin][3] format, which offers significant flexibility, allowing for the storage of additional metadata and supporting a broader range of index structures.\nversioned_docs/version-1.0/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\nversioned_docs/version-1.0/user-guide/logs/manage-pipelines.md:392: index: skipping\nversioned_docs/version-1.0/user-guide/concepts/features-that-you-concern.md:46:- **Flexible Indexing**: GreptimeDB supports on-demand manual index creation. You can create various index types (inverted, full-text, skipping) for both tag and field columns as needed, rather than automatically indexing every column. This allows you to optimize query performance while minimizing index overhead. Learn more in the [index documentation](/user-guide/manage-data/data-index.md).\nversioned_docs/version-1.0/user-guide/concepts/why-greptimedb.md:47:GreptimeDB is written in pure Rust for superior performance and reliability. The powerful and fast query engine is powered by vectorized execution and distributed parallel processing (thanks to [Apache DataFusion](https://datafusion.apache.org/)), and combined with [indexing capabilities](/user-guide/manage-data/data-index.md) such as inverted index, skipping index, and full-text index. GreptimeDB combines smart indexing and Massively Parallel Processing (MPP) to boost pruning and filtering.\nversioned_docs/version-1.0/user-guide/traces/data-model.md:188:We include [skipping\nversioned_docs/version-1.0/user-guide/traces/data-model.md:189:index](/user-guide/manage-data/data-index.md#skipping-index) on `service_name`\nversioned_docs/version-1.0/user-guide/manage-data/data-index.md:2:keywords: [index, inverted index, skipping index, full-text index, query performance]\nversioned_docs/version-1.0/user-guide/manage-data/data-index.md:3:description: Learn about different types of indexes in GreptimeDB, including inverted index, skipping index, and full-text index, and how to use them effectively to optimize query performance.\nversioned_docs/version-1.0/user-guide/manage-data/data-index.md:42:However, when a column has very high cardinality, the inverted index may not be the best choice due to the overhead of maintaining the index. It may bring high memory consumption and large index size. In this case, you may consider using the skipping index.\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/contributor-guide/datanode/data-persistence-indexing.md:40:索引文件采用 [Puffin][3] 格式，这种格式具有较大的灵活性，能够存储更多的元数据，并支持更多的索引结构。\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\nversioned_docs/version-1.0/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\nversioned_docs/version-1.0/user-guide/overview.md:62:Indexes such as inverted indexes, skipping indexes, and full-text indexes can significantly enhance query performance.\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/logs/manage-pipelines.md:390: index: skipping\nversioned_docs/version-1.0/user-guide/ingest-data/for-observability/prometheus.md:312:### Enable skipping index\nversioned_docs/version-1.0/user-guide/ingest-data/for-observability/prometheus.md:314:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-1.0/user-guide/ingest-data/for-observability/prometheus.md:316:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-1.0/user-guide/ingest-data/for-observability/prometheus.md:327: \"index.type\" = \"skipping\"\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/traces/data-model.md:173:引](/user-guide/manage-data/data-index.md#skipping-index)，满足常见的查询场景。\nversioned_docs/version-1.0/user-guide/migrate-to-greptimedb/migrate-from-clickhouse.md:71:> The choice of primary key and the granularity of the time index should be carefully planned based on your business's data volume and query scenarios. If the host cardinality is high (e.g., hundreds of thousands of monitored hosts), you should remove it from the primary key and consider creating a skipping index for it.\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\nversioned_docs/version-1.0/user-guide/deployments-administration/performance-tuning/design-table.md:2:keywords: [table schema, data model, cardinality, tag columns, field columns, time index, primary key, inverted index, full-text index, skipping index, append-only tables, data updating, wide table, distributed tables, partitioning]\nversioned_docs/version-1.0/user-guide/deployments-administration/performance-tuning/design-table.md:201:For high cardinality columns like `trace_id`, `request_id`, using a [skipping index](/user-guide/manage-data/data-index.md#skipping-index) is more appropriate.\nversioned_docs/version-1.0/user-guide/deployments-administration/performance-tuning/design-table.md:221:The following query can use the skipping index to filter the `request_id` column.\nversioned_docs/version-1.0/user-guide/deployments-administration/performance-tuning/design-table.md:227:However, note that the query capabilities of the skipping index are generally inferior to those of the inverted index.\nversioned_docs/version-1.0/user-guide/deployments-administration/manage-data/compaction.md:23:![SST layout](/compaction-sst-file-layout.jpg)\nversioned_docs/version-1.0/user-guide/deployments-administration/manage-data/region-failover.md:47:

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/ingest-data/for-observability/prometheus.md:301:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/ingest-data/for-observability/prometheus.md:314: \"index.type\" = \"skipping\"\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/deployments-administration/manage-data/compaction.md:22:![SST layout](/compaction-sst-file-layout.jpg)\ni18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/deployments-administration/manage-data/region-failover.md:50:

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

\nversioned_docs/version-0.13/reference/sql/limit.md:61:`LIMIT n, m` allows to select the m rows from the result after skipping the first n rows. The `LIMIT m OFFSET n` syntax\nversioned_docs/version-0.13/reference/sql/alter.md:174:Enable skipping index on a column:\nversioned_docs/version-0.13/reference/sql/alter.md:180:The valid options for the skipping index include:\nversioned_docs/version-0.13/reference/sql/alter.md:197:Remove the skipping index:\nversioned_docs/version-0.13/reference/sql/alter.md:209:If the fulltext index has never been enabled, you can enable it and specify the `analyzer` and `case_sensitive` options. When the fulltext index is already enabled on a column, you can disable it but **cannot modify the options, and so does the skipping index**.\nversioned_docs/version-0.13/reference/sql/create.md:113:| `index.type` | Index type | **Only for metric engine** String value, supports `none`, `skipping`. |\nversioned_docs/version-0.13/reference/sql/create.md:255:#### Create a physical table with enable skipping index for columns\nversioned_docs/version-0.13/reference/sql/create.md:257:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-0.13/reference/sql/create.md:259:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-0.13/reference/sql/create.md:270: \"index.type\" = \"skipping\",\ni18n/zh/docusaurus-plugin-content-docs/version-0.13/reference/sql/create.md:116:| `index.type` | Index 类型 | **仅用于 metric engine** 字符串值，支持 `none`, `skipping`. |\ni18n/zh/docusaurus-plugin-content-docs/version-0.13/reference/sql/create.md:263:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-0.13/reference/sql/create.md:276: \"index.type\" = \"skipping\",\nversioned_docs/version-0.13/contributor-guide/datanode/data-persistence-indexing.md:30:Apache Parquet file format provides inherent statistics in headers of column chunks and data pages, which are used for pruning and skipping.\nversioned_docs/version-0.13/contributor-guide/datanode/data-persistence-indexing.md:40:The index files utilize the [Puffin][3] format, which offers significant flexibility, allowing for the storage of additional metadata and supporting a broader range of index structures.\nversioned_docs/version-0.13/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\nversioned_docs/version-0.13/user-guide/logs/pipeline-config.md:653:- `skipping`: Specifies a column to use the skipping index type. The column must be of string type.\nversioned_docs/version-0.13/user-guide/logs/pipeline-config.md:673:Specify which field uses the skipping index. This index speeds up the query on high cardinality fields but consumes far less storage for building index files. Refer to the [Transform Example](#transform-example) below for syntax.\nversioned_docs/version-0.13/user-guide/logs/pipeline-config.md:710: index: skipping\nversioned_docs/version-0.13/user-guide/concepts/why-greptimedb.md:19:GreptimeDB is written in pure Rust for superior performance and reliability. The powerful and fast query engine is powered by vectorized execution and distributed parallel processing (Thanks to [Apache DataFusion](https://datafusion.apache.org/)), and combined with [indexing capabilities](/user-guide/manage-data/data-index.md) such as inverted index, data skipping index and full-text index, etc. GreptimeDB builds smart indexing and Massively Parallel Processing (MPP) together to boost pruning and filtering.\nversioned_docs/version-0.13/user-guide/manage-data/data-index.md:2:keywords: [index, inverted index, skipping index, fulltext index, query performance]\nversioned_docs/version-0.13/user-guide/manage-data/data-index.md:3:description: Learn about different types of indexes in GreptimeDB, including inverted index, skipping index, and fulltext index, and how to use them effectively to optimize query performance.\nversioned_docs/version-0.13/user-guide/manage-data/data-index.md:41:However, when you have a large number of unique tag values (Cartesian product among all columns indexed by inverted index), the inverted index may not be the best choice due to the overhead of maintaining the index. It may bring high memory consumption and large index size. In this case, you may consider using the skipping index.\ni18n/zh/docusaurus-plugin-content-docs/version-0.13/contributor-guide/datanode/data-persistence-indexing.md:40:索引文件采用 [Puffin][3] 格式，这种格式具有较大的灵活性，能够存储更多的元数据，并支持更多的索引结构。\ni18n/zh/docusaurus-plugin-content-docs/version-0.13/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\nversioned_docs/version-0.13/user-guide/administration/design-table.md:2:keywords: [table schema, data model, cardinality, tag columns, field columns, time index, primary key, inverted index, full-text index, skipping index, append-only tables, data updating, wide table, distributed tables, partitioning]\nversioned_docs/version-0.13/user-guide/administration/design-table.md:180:For high cardinality columns like `trace_id`, `request_id`, using a [skipping index](/user-guide/manage-data/data-index.md#skipping-index) is more appropriate.\nversioned_docs/version-0.13/user-guide/administration/design-table.md:200:The following query can use the skipping index to filter the `request_id` column.\nversioned_docs/version-0.13/user-guide/administration/design-table.md:206:However, note that the query capabilities of the skipping index are generally inferior to those of the inverted index.\nversioned_docs/version-0.13/user-guide/administration/manage-data/compaction.md:23:![SST layout](/compaction-sst-file-layout.jpg)\nversioned_docs/version-0.13/user-guide/administration/manage-data/region-failover.md:50:

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

\ni18n/zh/docusaurus-plugin-content-docs/version-0.13/user-guide/logs/pipeline-config.md:665:- `skipping`: 用于指定某列使用 skipping 类型的索引（跳数索引），该列需要是字符串类型\ni18n/zh/docusaurus-plugin-content-docs/version-0.13/user-guide/logs/pipeline-config.md:686:通过 `index: skipping` 指定在哪个列上建立跳数索引，该索引只需少量存储空间的索引文件即可以加速在高基数列上的查询，写法请参考下方的 [Transform 示例](#transform-示例)。\ni18n/zh/docusaurus-plugin-content-docs/version-0.13/user-guide/logs/pipeline-config.md:723: index: skipping\nversioned_docs/version-0.13/user-guide/administration/upgrade.md:188:GreptimeDB changed the `CREATE TABLE` statement in `v0.12`. You can only use column constraints to create inverted, skipping and fulltext index.\nversioned_docs/version-0.13/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\nversioned_docs/version-0.13/user-guide/ingest-data/for-observability/prometheus.md:163:### Enable skipping index\nversioned_docs/version-0.13/user-guide/ingest-data/for-observability/prometheus.md:165:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-0.13/user-guide/ingest-data/for-observability/prometheus.md:167:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-0.13/user-guide/ingest-data/for-observability/prometheus.md:178: \"index.type\" = \"skipping\"\ni18n/zh/docusaurus-plugin-content-docs/version-0.13/user-guide/administration/manage-data/compaction.md:22:![SST layout](/compaction-sst-file-layout.jpg)\ni18n/zh/docusaurus-plugin-content-docs/version-0.13/user-guide/administration/manage-data/region-failover.md:54:

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

\ni18n/zh/docusaurus-plugin-content-docs/version-0.13/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\ni18n/zh/docusaurus-plugin-content-docs/version-0.13/user-guide/ingest-data/for-observability/prometheus.md:157:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-0.13/user-guide/ingest-data/for-observability/prometheus.md:170: \"index.type\" = \"skipping\"\nversioned_docs/version-0.14/reference/sql/limit.md:61:`LIMIT n, m` allows to select the m rows from the result after skipping the first n rows. The `LIMIT m OFFSET n` syntax\nversioned_docs/version-0.14/reference/sql/alter.md:180:Enable skipping index on a column:\nversioned_docs/version-0.14/reference/sql/alter.md:186:The valid options for the skipping index include:\nversioned_docs/version-0.14/reference/sql/alter.md:203:Remove the skipping index:\nversioned_docs/version-0.14/reference/sql/alter.md:215:If the fulltext index has never been enabled, you can enable it and specify the `analyzer` and `case_sensitive` options. When the fulltext index is already enabled on a column, you can disable it but **cannot modify the options, and so does the skipping index**.\nversioned_docs/version-0.14/reference/sql/create.md:118:| `index.type` | Index type | **Only for metric engine** String value, supports `none`, `skipping`. |\nversioned_docs/version-0.14/reference/sql/create.md:260:#### Create a physical table with enable skipping index for columns\nversioned_docs/version-0.14/reference/sql/create.md:262:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-0.14/reference/sql/create.md:264:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-0.14/reference/sql/create.md:275: \"index.type\" = \"skipping\",\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/reference/sql/create.md:119:| `index.type` | Index 类型 | **仅用于 metric engine** 字符串值，支持 `none`, `skipping`. |\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/reference/sql/create.md:267:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/reference/sql/create.md:280: \"index.type\" = \"skipping\",\nversioned_docs/version-0.14/contributor-guide/datanode/data-persistence-indexing.md:30:Apache Parquet file format provides inherent statistics in headers of column chunks and data pages, which are used for pruning and skipping.\nversioned_docs/version-0.14/contributor-guide/datanode/data-persistence-indexing.md:40:The index files utilize the [Puffin][3] format, which offers significant flexibility, allowing for the storage of additional metadata and supporting a broader range of index structures.\nversioned_docs/version-0.14/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\nversioned_docs/version-0.14/user-guide/logs/pipeline-config.md:749:- `skipping`: Specifies a column to use the skipping index type. The column must be of string type.\nversioned_docs/version-0.14/user-guide/logs/pipeline-config.md:769:Specify which field uses the skipping index. This index speeds up the query on high cardinality fields but consumes far less storage for building index files. Refer to the [Transform Example](#transform-example) below for syntax.\nversioned_docs/version-0.14/user-guide/logs/pipeline-config.md:806: index: skipping\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/contributor-guide/datanode/data-persistence-indexing.md:40:索引文件采用 [Puffin][3] 格式，这种格式具有较大的灵活性，能够存储更多的元数据，并支持更多的索引结构。\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\nversioned_docs/version-0.14/user-guide/concepts/why-greptimedb.md:30:GreptimeDB is written in pure Rust for superior performance and reliability. The powerful and fast query engine is powered by vectorized execution and distributed parallel processing (thanks to [Apache DataFusion](https://datafusion.apache.org/)), and combined with [indexing capabilities](/user-guide/manage-data/data-index.md) such as inverted index, skipping index, and full-text index. GreptimeDB combines smart indexing and Massively Parallel Processing (MPP) to boost pruning and filtering.\nversioned_docs/version-0.14/user-guide/traces/data-model.md:180:We include [skipping\nversioned_docs/version-0.14/user-guide/traces/data-model.md:181:index](/user-guide/manage-data/data-index.md#skipping-index) on `service_name`\nversioned_docs/version-0.14/user-guide/manage-data/data-index.md:2:keywords: [index, inverted index, skipping index, fulltext index, query performance]\nversioned_docs/version-0.14/user-guide/manage-data/data-index.md:3:description: Learn about different types of indexes in GreptimeDB, including inverted index, skipping index, and fulltext index, and how to use them effectively to optimize query performance.\nversioned_docs/version-0.14/user-guide/manage-data/data-index.md:42:However, when you have a large number of unique tag values (Cartesian product among all columns indexed by inverted index), the inverted index may not be the best choice due to the overhead of maintaining the index. It may bring high memory consumption and large index size. In this case, you may consider using the skipping index.\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/user-guide/logs/pipeline-config.md:769:- `skipping`: 用于指定某列使用 skipping 类型的索引（跳数索引），该列需要是字符串类型\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/user-guide/logs/pipeline-config.md:790:通过 `index: skipping` 指定在哪个列上建立跳数索引，该索引只需少量存储空间的索引文件即可以加速在高基数列上的查询，写法请参考下方的 [Transform 示例](#transform-示例)。\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/user-guide/logs/pipeline-config.md:827: index: skipping\nversioned_docs/version-0.14/user-guide/administration/design-table.md:2:keywords: [table schema, data model, cardinality, tag columns, field columns, time index, primary key, inverted index, full-text index, skipping index, append-only tables, data updating, wide table, distributed tables, partitioning]\nversioned_docs/version-0.14/user-guide/administration/design-table.md:180:For high cardinality columns like `trace_id`, `request_id`, using a [skipping index](/user-guide/manage-data/data-index.md#skipping-index) is more appropriate.\nversioned_docs/version-0.14/user-guide/administration/design-table.md:200:The following query can use the skipping index to filter the `request_id` column.\nversioned_docs/version-0.14/user-guide/administration/design-table.md:206:However, note that the query capabilities of the skipping index are generally inferior to those of the inverted index.\nversioned_docs/version-0.14/user-guide/administration/manage-data/compaction.md:23:![SST layout](/compaction-sst-file-layout.jpg)\nversioned_docs/version-0.14/user-guide/administration/manage-data/region-failover.md:50:

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/user-guide/traces/data-model.md:172:引](/user-guide/manage-data/data-index.md#skipping-index)，满足常见的查询场景。\nversioned_docs/version-0.14/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\nversioned_docs/version-0.14/user-guide/overview.md:62:Indexes such as inverted indexes, skipping indexes, and full-text indexes can significantly enhance query performance.\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/user-guide/administration/manage-data/compaction.md:22:![SST layout](/compaction-sst-file-layout.jpg)\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/user-guide/administration/manage-data/region-failover.md:54:

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

\nversioned_docs/version-0.14/user-guide/ingest-data/for-observability/prometheus.md:163:### Enable skipping index\nversioned_docs/version-0.14/user-guide/ingest-data/for-observability/prometheus.md:165:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-0.14/user-guide/ingest-data/for-observability/prometheus.md:167:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-0.14/user-guide/ingest-data/for-observability/prometheus.md:178: \"index.type\" = \"skipping\"\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\nversioned_docs/version-0.14/user-guide/migrate-to-greptimedb/migrate-from-clickhouse.md:71:> The choice of primary key and the granularity of the time index should be carefully planned based on your business's data volume and query scenarios. If the host cardinality is high (e.g., hundreds of thousands of monitored hosts), you should remove it from the primary key and consider creating a skipping index for it.\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/user-guide/ingest-data/for-observability/prometheus.md:157:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-0.14/user-guide/ingest-data/for-observability/prometheus.md:170: \"index.type\" = \"skipping\"\nversioned_docs/version-0.15/reference/sql/limit.md:61:`LIMIT n, m` allows to select the m rows from the result after skipping the first n rows. The `LIMIT m OFFSET n` syntax\nversioned_docs/version-0.15/reference/sql/offset.md:2:keywords: [SQL OFFSET clause, data retrieval, skipping rows]\nversioned_docs/version-0.15/reference/sql/alter.md:173:Enable skipping index on a column:\nversioned_docs/version-0.15/reference/sql/alter.md:179:The valid options for the skipping index include:\nversioned_docs/version-0.15/reference/sql/alter.md:196:Remove the skipping index:\nversioned_docs/version-0.15/reference/sql/alter.md:208:If the fulltext index has never been enabled, you can enable it and specify the `analyzer` and `case_sensitive` options. When the fulltext index is already enabled on a column, you can disable it but **cannot modify the options, and so does the skipping index**.\nversioned_docs/version-0.15/reference/sql/create.md:117:| `index.type` | Index type | **Only for metric engine** String value, supports `none`, `skipping`. |\nversioned_docs/version-0.15/reference/sql/create.md:256:#### Create a physical table with enable skipping index for columns\nversioned_docs/version-0.15/reference/sql/create.md:258:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-0.15/reference/sql/create.md:260:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-0.15/reference/sql/create.md:271: \"index.type\" = \"skipping\",\nversioned_docs/version-0.15/reference/sql/create.md:288:| SKIPPING INDEX | Creates a skipping index to speed up query on sparse data. |\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/reference/sql/create.md:118:| `index.type` | Index 类型 | **仅用于 metric engine** 字符串值，支持 `none`, `skipping`. |\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/reference/sql/create.md:263:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/reference/sql/create.md:276: \"index.type\" = \"skipping\",\nversioned_docs/version-0.15/contributor-guide/datanode/data-persistence-indexing.md:30:Apache Parquet file format provides inherent statistics in headers of column chunks and data pages, which are used for pruning and skipping.\nversioned_docs/version-0.15/contributor-guide/datanode/data-persistence-indexing.md:40:The index files utilize the [Puffin][3] format, which offers significant flexibility, allowing for the storage of additional metadata and supporting a broader range of index structures.\nversioned_docs/version-0.15/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\nversioned_docs/version-0.15/user-guide/logs/pipeline-config.md:959:- `skipping`: Specifies a column to use the skipping index type. The column must be of string type.\nversioned_docs/version-0.15/user-guide/logs/pipeline-config.md:979:Specify which field uses the skipping index. This index speeds up the query on high cardinality fields but consumes far less storage for building index files. Refer to the [Transform Example](#transform-example) below for syntax.\nversioned_docs/version-0.15/user-guide/logs/pipeline-config.md:1016: index: skipping\nversioned_docs/version-0.15/user-guide/logs/fulltext-index-config.md:12:GreptimeDB provides full-text indexing capabilities to accelerate text search operations. You can configure full-text index when creating or altering tables, with various options to optimize for different use cases. For a general introduction to different types of indexes in GreptimeDB, including inverted index and skipping index, please refer to the [Data Index](/user-guide/manage-data/data-index) guide.\nversioned_docs/version-0.15/user-guide/concepts/why-greptimedb.md:30:GreptimeDB is written in pure Rust for superior performance and reliability. The powerful and fast query engine is powered by vectorized execution and distributed parallel processing (thanks to [Apache DataFusion](https://datafusion.apache.org/)), and combined with [indexing capabilities](/user-guide/manage-data/data-index.md) such as inverted index, skipping index, and full-text index. GreptimeDB combines smart indexing and Massively Parallel Processing (MPP) to boost pruning and filtering.\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/contributor-guide/datanode/data-persistence-indexing.md:40:索引文件采用 [Puffin][3] 格式，这种格式具有较大的灵活性，能够存储更多的元数据，并支持更多的索引结构。\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\nversioned_docs/version-0.15/user-guide/traces/data-model.md:180:We include [skipping\nversioned_docs/version-0.15/user-guide/traces/data-model.md:181:index](/user-guide/manage-data/data-index.md#skipping-index) on `service_name`\nversioned_docs/version-0.15/user-guide/manage-data/data-index.md:2:keywords: [index, inverted index, skipping index, fulltext index, query performance]\nversioned_docs/version-0.15/user-guide/manage-data/data-index.md:3:description: Learn about different types of indexes in GreptimeDB, including inverted index, skipping index, and fulltext index, and how to use them effectively to optimize query performance.\nversioned_docs/version-0.15/user-guide/manage-data/data-index.md:42:However, when you have a large number of unique tag values (Cartesian product among all columns indexed by inverted index), the inverted index may not be the best choice due to the overhead of maintaining the index. It may bring high memory consumption and large index size. In this case, you may consider using the skipping index.\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/user-guide/logs/pipeline-config.md:976:- `skipping`: 用于指定某列使用 skipping 类型的索引（跳数索引），该列需要是字符串类型\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/user-guide/logs/pipeline-config.md:997:通过 `index: skipping` 指定在哪个列上建立跳数索引，该索引只需少量存储空间的索引文件即可以加速在高基数列上的查询，写法请参考下方的 [Transform 示例](#transform-示例)。\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/user-guide/logs/pipeline-config.md:1034: index: skipping\nversioned_docs/version-0.15/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\nversioned_docs/version-0.15/user-guide/overview.md:62:Indexes such as inverted indexes, skipping indexes, and full-text indexes can significantly enhance query performance.\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/user-guide/traces/data-model.md:172:引](/user-guide/manage-data/data-index.md#skipping-index)，满足常见的查询场景。\nversioned_docs/version-0.15/user-guide/ingest-data/for-observability/prometheus.md:308:### Enable skipping index\nversioned_docs/version-0.15/user-guide/ingest-data/for-observability/prometheus.md:310:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-0.15/user-guide/ingest-data/for-observability/prometheus.md:312:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-0.15/user-guide/ingest-data/for-observability/prometheus.md:323: \"index.type\" = \"skipping\"\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\nversioned_docs/version-0.15/user-guide/migrate-to-greptimedb/migrate-from-clickhouse.md:71:> The choice of primary key and the granularity of the time index should be carefully planned based on your business's data volume and query scenarios. If the host cardinality is high (e.g., hundreds of thousands of monitored hosts), you should remove it from the primary key and consider creating a skipping index for it.\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/user-guide/ingest-data/for-observability/prometheus.md:297:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/user-guide/ingest-data/for-observability/prometheus.md:310: \"index.type\" = \"skipping\"\nversioned_docs/version-0.15/user-guide/deployments-administration/performance-tuning/design-table.md:2:keywords: [table schema, data model, cardinality, tag columns, field columns, time index, primary key, inverted index, full-text index, skipping index, append-only tables, data updating, wide table, distributed tables, partitioning]\nversioned_docs/version-0.15/user-guide/deployments-administration/performance-tuning/design-table.md:180:For high cardinality columns like `trace_id`, `request_id`, using a [skipping index](/user-guide/manage-data/data-index.md#skipping-index) is more appropriate.\nversioned_docs/version-0.15/user-guide/deployments-administration/performance-tuning/design-table.md:200:The following query can use the skipping index to filter the `request_id` column.\nversioned_docs/version-0.15/user-guide/deployments-administration/performance-tuning/design-table.md:206:However, note that the query capabilities of the skipping index are generally inferior to those of the inverted index.\nversioned_docs/version-0.15/user-guide/deployments-administration/manage-data/compaction.md:23:![SST layout](/compaction-sst-file-layout.jpg)\nversioned_docs/version-0.15/user-guide/deployments-administration/manage-data/region-failover.md:47:

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/user-guide/deployments-administration/manage-data/compaction.md:22:![SST layout](/compaction-sst-file-layout.jpg)\ni18n/zh/docusaurus-plugin-content-docs/version-0.15/user-guide/deployments-administration/manage-data/region-failover.md:50:

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

\nversioned_docs/version-0.12/reference/sql/limit.md:61:`LIMIT n, m` allows to select the m rows from the result after skipping the first n rows. The `LIMIT m OFFSET n` syntax\nversioned_docs/version-0.12/reference/sql/create.md:113:| `index.type` | Index type | **Only for metric engine** String value, supports `none`, `skipping`. |\nversioned_docs/version-0.12/reference/sql/create.md:255:#### Create a physical table with enable skipping index for columns\nversioned_docs/version-0.12/reference/sql/create.md:257:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-0.12/reference/sql/create.md:259:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-0.12/reference/sql/create.md:270: \"index.type\" = \"skipping\",\ni18n/zh/docusaurus-plugin-content-docs/current/reference/pipeline/pipeline-config.md:1090:- `skipping`: 用于指定某列使用 skipping 类型的索引（跳数索引）\ni18n/zh/docusaurus-plugin-content-docs/current/reference/pipeline/pipeline-config.md:1109:只有 `fulltext` 和 `skipping` 支持 `options`。\ni18n/zh/docusaurus-plugin-content-docs/current/reference/pipeline/pipeline-config.md:1145:通过 `index: skipping` 指定在哪个列上建立跳数索引，该索引只需少量存储空间的索引文件即可以加速在高基数列上的查询。\ni18n/zh/docusaurus-plugin-content-docs/current/reference/pipeline/pipeline-config.md:1146:与 `fulltext` 不同，`skipping` 不仅限于字符串类型列。\ni18n/zh/docusaurus-plugin-content-docs/current/reference/pipeline/pipeline-config.md:1153: type: skipping\ni18n/zh/docusaurus-plugin-content-docs/current/reference/pipeline/pipeline-config.md:1195: index: skipping\ni18n/zh/docusaurus-plugin-content-docs/current/reference/sql/information-schema/ssts-index-meta.md:2:keywords: [SST 索引元数据, Puffin 索引, 倒排索引, 全文索引, 布隆过滤器, 索引元数据]\ni18n/zh/docusaurus-plugin-content-docs/current/reference/sql/information-schema/ssts-index-meta.md:3:description: 提供对 SST（排序字符串表）索引元数据的访问，包括以 Puffin 格式存储的倒排索引、全文索引和布隆过滤器的信息。\ni18n/zh/docusaurus-plugin-content-docs/current/reference/sql/information-schema/ssts-index-meta.md:8:`SSTS_INDEX_META` 表提供对从清单中收集的 SST（排序字符串表）索引元数据的访问。该表显示 Puffin 索引元数据的信息，包括倒排索引、全文索引和布隆过滤器。\ni18n/zh/docusaurus-plugin-content-docs/current/reference/sql/information-schema/ssts-index-meta.md:42:- `index_file_path`：Puffin 索引文件的完整路径。\nversioned_docs/version-0.12/contributor-guide/datanode/data-persistence-indexing.md:30:Apache Parquet file format provides inherent statistics in headers of column chunks and data pages, which are used for pruning and skipping.\nversioned_docs/version-0.12/contributor-guide/datanode/data-persistence-indexing.md:40:The index files utilize the [Puffin][3] format, which offers significant flexibility, allowing for the storage of additional metadata and supporting a broader range of index structures.\nversioned_docs/version-0.12/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\ni18n/zh/docusaurus-plugin-content-docs/current/reference/sql/create.md:164:| `index.type` | Index 类型 | **仅用于 metric engine** 字符串值，支持 `none`, `skipping`. |\ni18n/zh/docusaurus-plugin-content-docs/current/reference/sql/create.md:321:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/current/reference/sql/create.md:334: \"index.type\" = \"skipping\",\nversioned_docs/version-0.12/user-guide/concepts/why-greptimedb.md:19:GreptimeDB is written in pure Rust for superior performance and reliability. The powerful and fast query engine is powered by vectorized execution and distributed parallel processing (Thanks to [Apache DataFusion](https://datafusion.apache.org/)), and combined with [indexing capabilities](/user-guide/manage-data/data-index.md) such as inverted index, data skipping index and full-text index, etc. GreptimeDB builds smart indexing and Massively Parallel Processing (MPP) together to boost pruning and filtering. read the [benchmark reports](https://www.greptime.com/blogs/2024-09-09-report-summary).\nversioned_docs/version-0.12/user-guide/manage-data/data-index.md:2:keywords: [index, inverted index, skipping index, fulltext index, query performance]\nversioned_docs/version-0.12/user-guide/manage-data/data-index.md:3:description: Learn about different types of indexes in GreptimeDB, including inverted index, skipping index, and fulltext index, and how to use them effectively to optimize query performance.\nversioned_docs/version-0.12/user-guide/manage-data/data-index.md:41:However, when you have a large number of unique tag values (Cartesian product among all columns indexed by inverted index), the inverted index may not be the best choice due to the overhead of maintaining the index. It may bring high memory consumption and large index size. In this case, you may consider using the skipping index.\nversioned_docs/version-0.12/user-guide/administration/design-table.md:2:keywords: [table schema, data model, cardinality, tag columns, field columns, time index, primary key, inverted index, full-text index, skipping index, append-only tables, data updating, wide table, distributed tables, partitioning]\nversioned_docs/version-0.12/user-guide/administration/design-table.md:170:using a [skipping index](/user-guide/manage-data/data-index.md#skipping-index) is more appropriate.\nversioned_docs/version-0.12/user-guide/administration/design-table.md:185:In this example, the skipping index is applied to the `device_id` column.\nversioned_docs/version-0.12/user-guide/administration/design-table.md:186:However, note that the query efficiency and capability of the skipping index are generally inferior to those of the full-text index and inverted index.\nversioned_docs/version-0.12/user-guide/administration/design-table.md:203:3. **Alternative Indexing**: For columns with high selectivity, consider using a skipping index (`SKIPPING INDEX`) to enhance filtering query performance.\nversioned_docs/version-0.12/user-guide/administration/manage-data/compaction.md:23:![SST layout](/compaction-sst-file-layout.jpg)\nversioned_docs/version-0.12/user-guide/administration/manage-data/region-failover.md:50:

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

\nversioned_docs/version-0.12/user-guide/administration/upgrade.md:188:GreptimeDB changed the `CREATE TABLE` statement in `v0.12`. You can only use column constraints to create inverted, skipping and fulltext index.\nversioned_docs/version-0.12/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\nversioned_docs/version-0.12/user-guide/ingest-data/for-observability/prometheus.md:163:### Enable skipping index\nversioned_docs/version-0.12/user-guide/ingest-data/for-observability/prometheus.md:165:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-0.12/user-guide/ingest-data/for-observability/prometheus.md:167:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-0.12/user-guide/ingest-data/for-observability/prometheus.md:178: \"index.type\" = \"skipping\"\ni18n/zh/docusaurus-plugin-content-docs/current/contributor-guide/datanode/data-persistence-indexing.md:40:索引文件采用 [Puffin][3] 格式，这种格式具有较大的灵活性，能够存储更多的元数据，并支持更多的索引结构。\ni18n/zh/docusaurus-plugin-content-docs/current/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\ni18n/zh/docusaurus-plugin-content-docs/current/user-guide/logs/manage-pipelines.md:390: index: skipping\ni18n/zh/docusaurus-plugin-content-docs/current/user-guide/traces/data-model.md:178:引](/user-guide/manage-data/data-index.md#skipping-index)，满足常见的查询场景。\nversioned_docs/version-0.17/reference/pipeline/pipeline-config.md:1002:- `skipping`: Specifies a column to use the skipping index type. The column must be of string type.\nversioned_docs/version-0.17/reference/pipeline/pipeline-config.md:1022:Specify which field uses the skipping index. This index speeds up the query on high cardinality fields but consumes far less storage for building index files. Refer to the [Transform Example](#transform-example) below for syntax.\nversioned_docs/version-0.17/reference/pipeline/pipeline-config.md:1059: index: skipping\ni18n/zh/docusaurus-plugin-content-docs/current/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\ni18n/zh/docusaurus-plugin-content-docs/current/user-guide/ingest-data/for-observability/prometheus.md:334:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/current/user-guide/ingest-data/for-observability/prometheus.md:347: \"index.type\" = \"skipping\"\nversioned_docs/version-0.17/reference/sql/limit.md:61:`LIMIT n, m` allows to select the m rows from the result after skipping the first n rows. The `LIMIT m OFFSET n` syntax\nversioned_docs/version-0.17/reference/sql/offset.md:2:keywords: [SQL OFFSET clause, data retrieval, skipping rows]\nversioned_docs/version-0.17/reference/sql/alter.md:201:Enable skipping index on a column:\nversioned_docs/version-0.17/reference/sql/alter.md:207:The valid options for the skipping index include:\nversioned_docs/version-0.17/reference/sql/alter.md:224:Remove the skipping index:\nversioned_docs/version-0.17/reference/sql/alter.md:236:If the fulltext index has never been enabled, you can enable it and specify the `analyzer` and `case_sensitive` options. When the fulltext index is already enabled on a column, you can disable it but **cannot modify the options, and so does the skipping index**.\nversioned_docs/version-0.17/reference/sql/create.md:156:| `index.type` | Index type | **Only for metric engine** String value, supports `none`, `skipping`. |\nversioned_docs/version-0.17/reference/sql/create.md:296:#### Create a physical table with enable skipping index for columns\nversioned_docs/version-0.17/reference/sql/create.md:298:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-0.17/reference/sql/create.md:300:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-0.17/reference/sql/create.md:311: \"index.type\" = \"skipping\",\nversioned_docs/version-0.17/reference/sql/create.md:328:| SKIPPING INDEX | Creates a skipping index to speed up query on sparse data. |\ni18n/zh/docusaurus-plugin-content-docs/current/user-guide/deployments-administration/manage-data/compaction.md:22:![SST layout](/compaction-sst-file-layout.jpg)\ni18n/zh/docusaurus-plugin-content-docs/current/user-guide/deployments-administration/manage-data/region-failover.md:50:

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

\nversioned_docs/version-0.17/contributor-guide/datanode/data-persistence-indexing.md:30:Apache Parquet file format provides inherent statistics in headers of column chunks and data pages, which are used for pruning and skipping.\nversioned_docs/version-0.17/contributor-guide/datanode/data-persistence-indexing.md:40:The index files utilize the [Puffin][3] format, which offers significant flexibility, allowing for the storage of additional metadata and supporting a broader range of index structures.\nversioned_docs/version-0.17/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\nversioned_docs/version-0.17/user-guide/logs/manage-pipelines.md:383: index: skipping\nversioned_docs/version-0.17/user-guide/concepts/why-greptimedb.md:30:GreptimeDB is written in pure Rust for superior performance and reliability. The powerful and fast query engine is powered by vectorized execution and distributed parallel processing (thanks to [Apache DataFusion](https://datafusion.apache.org/)), and combined with [indexing capabilities](/user-guide/manage-data/data-index.md) such as inverted index, skipping index, and full-text index. GreptimeDB combines smart indexing and Massively Parallel Processing (MPP) to boost pruning and filtering.\nversioned_docs/version-0.17/user-guide/traces/data-model.md:180:We include [skipping\nversioned_docs/version-0.17/user-guide/traces/data-model.md:181:index](/user-guide/manage-data/data-index.md#skipping-index) on `service_name`\ni18n/zh/docusaurus-plugin-content-docs/version-0.12/reference/sql/create.md:116:| `index.type` | Index 类型 | **仅用于 metric engine** 字符串值，支持 `none`, `skipping`. |\ni18n/zh/docusaurus-plugin-content-docs/version-0.12/reference/sql/create.md:263:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-0.12/reference/sql/create.md:276: \"index.type\" = \"skipping\",\nversioned_docs/version-0.17/user-guide/manage-data/data-index.md:2:keywords: [index, inverted index, skipping index, full-text index, query performance]\nversioned_docs/version-0.17/user-guide/manage-data/data-index.md:3:description: Learn about different types of indexes in GreptimeDB, including inverted index, skipping index, and full-text index, and how to use them effectively to optimize query performance.\nversioned_docs/version-0.17/user-guide/manage-data/data-index.md:42:However, when you have a large number of unique tag values (Cartesian product among all columns indexed by inverted index), the inverted index may not be the best choice due to the overhead of maintaining the index. It may bring high memory consumption and large index size. In this case, you may consider using the skipping index.\nversioned_docs/version-0.17/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\nversioned_docs/version-0.17/user-guide/overview.md:62:Indexes such as inverted indexes, skipping indexes, and full-text indexes can significantly enhance query performance.\nversioned_docs/version-0.17/user-guide/ingest-data/for-observability/prometheus.md:312:### Enable skipping index\nversioned_docs/version-0.17/user-guide/ingest-data/for-observability/prometheus.md:314:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-0.17/user-guide/ingest-data/for-observability/prometheus.md:316:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-0.17/user-guide/ingest-data/for-observability/prometheus.md:327: \"index.type\" = \"skipping\"\ni18n/zh/docusaurus-plugin-content-docs/version-0.12/contributor-guide/datanode/data-persistence-indexing.md:40:索引文件采用 [Puffin][3] 格式，这种格式具有较大的灵活性，能够存储更多的元数据，并支持更多的索引结构。\ni18n/zh/docusaurus-plugin-content-docs/version-0.12/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\nversioned_docs/version-0.17/user-guide/migrate-to-greptimedb/migrate-from-clickhouse.md:71:> The choice of primary key and the granularity of the time index should be carefully planned based on your business's data volume and query scenarios. If the host cardinality is high (e.g., hundreds of thousands of monitored hosts), you should remove it from the primary key and consider creating a skipping index for it.\nversioned_docs/version-0.17/user-guide/deployments-administration/performance-tuning/design-table.md:2:keywords: [table schema, data model, cardinality, tag columns, field columns, time index, primary key, inverted index, full-text index, skipping index, append-only tables, data updating, wide table, distributed tables, partitioning]\nversioned_docs/version-0.17/user-guide/deployments-administration/performance-tuning/design-table.md:180:For high cardinality columns like `trace_id`, `request_id`, using a [skipping index](/user-guide/manage-data/data-index.md#skipping-index) is more appropriate.\nversioned_docs/version-0.17/user-guide/deployments-administration/performance-tuning/design-table.md:200:The following query can use the skipping index to filter the `request_id` column.\nversioned_docs/version-0.17/user-guide/deployments-administration/performance-tuning/design-table.md:206:However, note that the query capabilities of the skipping index are generally inferior to those of the inverted index.\nversioned_docs/version-0.17/user-guide/deployments-administration/manage-data/compaction.md:23:![SST layout](/compaction-sst-file-layout.jpg)\nversioned_docs/version-0.17/user-guide/deployments-administration/manage-data/region-failover.md:47:

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

\ni18n/zh/docusaurus-plugin-content-docs/version-0.12/user-guide/administration/manage-data/compaction.md:22:![SST layout](/compaction-sst-file-layout.jpg)\ni18n/zh/docusaurus-plugin-content-docs/version-0.12/user-guide/administration/manage-data/region-failover.md:54:

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

\ni18n/zh/docusaurus-plugin-content-docs/version-0.12/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\ndocs/reference/pipeline/pipeline-config.md:1074:- `skipping`: Specifies a column to use the skipping index type.\ndocs/reference/pipeline/pipeline-config.md:1093:Only `fulltext` and `skipping` support `options`.\ndocs/reference/pipeline/pipeline-config.md:1129:Specify which field uses the skipping index. This index speeds up the query on high cardinality fields but consumes far less storage for building index files.\ndocs/reference/pipeline/pipeline-config.md:1130:Unlike `fulltext`, `skipping` is not limited to string columns.\ndocs/reference/pipeline/pipeline-config.md:1131:Use the detailed form when you need to set skipping index options:\ndocs/reference/pipeline/pipeline-config.md:1137: type: skipping\ndocs/reference/pipeline/pipeline-config.md:1179: index: skipping\ni18n/zh/docusaurus-plugin-content-docs/version-0.12/user-guide/ingest-data/for-observability/prometheus.md:157:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-0.12/user-guide/ingest-data/for-observability/prometheus.md:170: \"index.type\" = \"skipping\"\ndocs/reference/sql/information-schema/ssts-index-meta.md:2:keywords: [SST index metadata, Puffin index, inverted index, fulltext index, bloom filter, index metadata]\ndocs/reference/sql/information-schema/ssts-index-meta.md:3:description: Provides access to SST (Sorted String Table) index metadata, including information about inverted indexes, fulltext indexes, and bloom filters stored in Puffin format.\ndocs/reference/sql/information-schema/ssts-index-meta.md:8:The `SSTS_INDEX_META` table provides access to SST (Sorted String Table) index metadata collected from the manifest. This table surfaces information about Puffin index metadata, including inverted indexes, fulltext indexes, and bloom filters.\ndocs/reference/sql/information-schema/ssts-index-meta.md:42:- `index_file_path`: The full path to the Puffin index file.\ndocs/reference/sql/limit.md:61:`LIMIT n, m` allows to select the m rows from the result after skipping the first n rows. The `LIMIT m OFFSET n` syntax\ndocs/reference/sql/offset.md:2:keywords: [SQL OFFSET clause, data retrieval, skipping rows]\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/reference/pipeline/pipeline-config.md:1018:- `skipping`: 用于指定某列使用 skipping 类型的索引（跳数索引），该列需要是字符串类型\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/reference/pipeline/pipeline-config.md:1039:通过 `index: skipping` 指定在哪个列上建立跳数索引，该索引只需少量存储空间的索引文件即可以加速在高基数列上的查询，写法请参考下方的 [Transform 示例](#transform-示例)。\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/reference/pipeline/pipeline-config.md:1076: index: skipping\ndocs/reference/sql/alter.md:300:Enable skipping index on a column:\ndocs/reference/sql/alter.md:306:The valid options for the skipping index include:\ndocs/reference/sql/alter.md:326:Remove the skipping index:\ndocs/reference/sql/alter.md:340:If the fulltext index has never been enabled, you can enable it and specify the `analyzer` and `case_sensitive` options. When the fulltext index is already enabled on a column, you can disable it but **cannot modify the options, and so does the skipping index**.\ndocs/reference/sql/create.md:164:| `index.type` | Index type | **Only for metric engine** String value, supports `none`, `skipping`. |\ndocs/reference/sql/create.md:315:#### Create a physical table with enable skipping index for columns\ndocs/reference/sql/create.md:317:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\ndocs/reference/sql/create.md:319:Create a physical table with a skipping index; all automatically added columns will have this index applied.\ndocs/reference/sql/create.md:330: \"index.type\" = \"skipping\",\ndocs/reference/sql/create.md:365:| SKIPPING INDEX | Creates a skipping index to speed up query on sparse data. |\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/reference/sql/create.md:157:| `index.type` | Index 类型 | **仅用于 metric engine** 字符串值，支持 `none`, `skipping`. |\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/reference/sql/create.md:303:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/reference/sql/create.md:316: \"index.type\" = \"skipping\",\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/contributor-guide/datanode/data-persistence-indexing.md:40:索引文件采用 [Puffin][3] 格式，这种格式具有较大的灵活性，能够存储更多的元数据，并支持更多的索引结构。\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\ndocs/getting-started/quick-start.md:106:For high-cardinality `trace_id`s, we have enabled the [skip index](/user-guide/manage-data/data-index.md#skipping-index).\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/user-guide/logs/manage-pipelines.md:381: index: skipping\ndocs/contributor-guide/datanode/storage-engine.md:32: - Rows in an SST are sorted by primary key and time index; see [Data Layout in SST Files](#data-layout-in-sst-files).\ndocs/contributor-guide/datanode/storage-engine.md:68:## Data Layout in SST Files\ndocs/contributor-guide/datanode/storage-engine.md:106: $\"SST$ \ndocs/contributor-guide/datanode/storage-engine.md:108:## Scan Pruning\ndocs/contributor-guide/datanode/storage-engine.md:114:3. **Indexes.** Inverted, skipping, and full-text indexes provide more selective pruning for predicates that statistics cannot resolve. See [Data Persistence and Indexing](data-persistence-indexing.md).\ndocs/contributor-guide/datanode/storage-engine.md:116: $\"Scan$ \ni18n/zh/docusaurus-plugin-content-docs/version-0.17/user-guide/traces/data-model.md:172:引](/user-guide/manage-data/data-index.md#skipping-index)，满足常见的查询场景。\ndocs/contributor-guide/datanode/data-persistence-indexing.md:30:Apache Parquet file format provides inherent statistics in headers of column chunks and data pages, which are used for pruning and skipping.\ndocs/contributor-guide/datanode/data-persistence-indexing.md:40:The index files utilize the [Puffin][3] format, which offers significant flexibility, allowing for the storage of additional metadata and supporting a broader range of index structures.\ndocs/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\ndocs/contributor-guide/datanode/data-persistence-indexing.md:44:GreptimeDB stores several index structures in the Puffin file as Blobs, including the inverted index, the skipping index (backed by a bloom filter), and the full-text index. The inverted index was the first one supported and is described in detail below.\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\ndocs/user-guide/logs/manage-pipelines.md:392: index: skipping\ndocs/user-guide/concepts/features-that-you-concern.md:46:- **Flexible Indexing**: GreptimeDB supports on-demand manual index creation. You can create various index types (inverted, full-text, skipping) for both tag and field columns as needed, rather than automatically indexing every column. This allows you to optimize query performance while minimizing index overhead. Learn more in the [index documentation](/user-guide/manage-data/data-index.md).\ndocs/user-guide/concepts/why-greptimedb.md:47:GreptimeDB is written in pure Rust for superior performance and reliability. The powerful and fast query engine is powered by vectorized execution and distributed parallel processing (thanks to [Apache DataFusion](https://datafusion.apache.org/)), and combined with [indexing capabilities](/user-guide/manage-data/data-index.md) such as inverted index, skipping index, and full-text index. GreptimeDB combines smart indexing and Massively Parallel Processing (MPP) to boost pruning and filtering.\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/user-guide/ingest-data/for-observability/prometheus.md:301:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/user-guide/ingest-data/for-observability/prometheus.md:314: \"index.type\" = \"skipping\"\ndocs/user-guide/traces/data-model.md:193:We include [skipping\ndocs/user-guide/traces/data-model.md:194:index](/user-guide/manage-data/data-index.md#skipping-index) on `service_name`\ndocs/user-guide/manage-data/data-index.md:2:keywords: [index, inverted index, skipping index, full-text index, query performance]\ndocs/user-guide/manage-data/data-index.md:3:description: Learn about different types of indexes in GreptimeDB, including inverted index, skipping index, and full-text index, and how to use them effectively to optimize query performance.\ndocs/user-guide/manage-data/data-index.md:42:However, when a column has very high cardinality, the inverted index may not be the best choice due to the overhead of maintaining the index. It may bring high memory consumption and large index size. In this case, you may consider using the skipping index.\ndocs/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/user-guide/deployments-administration/manage-data/compaction.md:22:![SST layout](/compaction-sst-file-layout.jpg)\ni18n/zh/docusaurus-plugin-content-docs/version-0.17/user-guide/deployments-administration/manage-data/region-failover.md:50:

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

\ndocs/user-guide/overview.md:62:Indexes such as inverted indexes, skipping indexes, and full-text indexes can significantly enhance query performance.\ndocs/user-guide/ingest-data/for-observability/prometheus.md:346:### Enable skipping index\ndocs/user-guide/ingest-data/for-observability/prometheus.md:348:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\ndocs/user-guide/ingest-data/for-observability/prometheus.md:350:Create a physical table with a skipping index; all automatically added columns will have this index applied.\ndocs/user-guide/ingest-data/for-observability/prometheus.md:361: \"index.type\" = \"skipping\"\ndocs/user-guide/migrate-to-greptimedb/migrate-from-clickhouse.md:71:> The choice of primary key and the granularity of the time index should be carefully planned based on your business's data volume and query scenarios. If the host cardinality is high (e.g., hundreds of thousands of monitored hosts), you should remove it from the primary key and consider creating a skipping index for it.\ndocs/user-guide/deployments-administration/performance-tuning/design-table.md:2:keywords: [table schema, data model, cardinality, tag columns, field columns, time index, primary key, inverted index, full-text index, skipping index, append-only tables, data updating, wide table, distributed tables, partitioning]\ndocs/user-guide/deployments-administration/performance-tuning/design-table.md:204:For high cardinality columns like `trace_id`, `request_id`, using a [skipping index](/user-guide/manage-data/data-index.md#skipping-index) is more appropriate.\ndocs/user-guide/deployments-administration/performance-tuning/design-table.md:224:The following query can use the skipping index to filter the `request_id` column.\ndocs/user-guide/deployments-administration/performance-tuning/design-table.md:230:However, note that the query capabilities of the skipping index are generally inferior to those of the inverted index.\ndocs/user-guide/deployments-administration/manage-data/compaction.md:23:![SST layout](/compaction-sst-file-layout.jpg)\ndocs/user-guide/deployments-administration/manage-data/region-failover.md:47:

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

\n",{"_956":2566,"_937":938,"_958":944},{"_993":2567,"_995":2568,"_997":2569,"_999":1000,"_942":31,"_1001":31,"_41":2563,"_1002":2570,"_1004":1005,"_949":112,"_91":1006},"versioned_docs/version-0.16/reference/sql/limit.md:61:`LIMIT n, m` allows to select the m rows from the result after skipping the first n rows. The `LIMIT m OFFSET n` syntax\nversioned_docs/version-0.16/reference/sql/offset.md:2:keywords: [SQL OFFSET clause, data retrieval, skipping rows]\nversioned_docs/version-0.16/reference/sql/alter.md:201:Enable skipping index on a column:\nversioned_docs/version-0.16/reference/sql/alter.md:207:The valid options for the skipping index include:\nversioned_docs/version-0.16/reference/sql/alter.md:224:Remove the skipping index:\nversioned_docs/version-0.16/reference/sql/alter.md:236:If the fulltext index has never been enabled, you can enable it and specify the `analyzer` and `case_sensitive` options. When the fulltext index is already enabled on a column, you can disable it but **cannot modify the options, and so does the skipping index**.\nversioned_docs/version-0.16/reference/sql/create.md:156:| `index.type` | Index type | **Only for metric engine** String value, supports `none`, `skipping`. |\nversioned_docs/version-0.16/reference/sql/create.md:296:#### Create a physical table with enable skipping index for columns\nversioned_docs/version-0.16/reference/sql/create.md:298:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-0.16/reference/sql/create.md:300:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-0.16/reference/sql/create.md:311: \"index.type\" = \"skipping\",\nversioned_docs/version-0.16/reference/sql/create.md:328:| SKIPPING INDEX | Creates a skipping index to speed up query on sparse data. |\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/reference/sql/create.md:157:| `index.type` | Index 类型 | **仅用于 metric engine** 字符串值，支持 `none`, `skipping`. |\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/reference/sql/create.md:303:默认情况下，metric engine 不会为列创建索引。你可以通过设置 `index.type` 为 `skipping` 来设置索引类型。\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/reference/sql/create.md:316: \"index.type\" = \"skipping\",\nversioned_docs/version-0.16/contributor-guide/datanode/data-persistence-indexing.md:30:Apache Parquet file format provides inherent statistics in headers of column chunks and data pages, which are used for pruning and skipping.\nversioned_docs/version-0.16/contributor-guide/datanode/data-persistence-indexing.md:40:The index files utilize the [Puffin][3] format, which offers significant flexibility, allowing for the storage of additional metadata and supporting a broader range of index structures.\nversioned_docs/version-0.16/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\nversioned_docs/version-0.16/user-guide/logs/pipeline-config.md:1000:- `skipping`: Specifies a column to use the skipping index type. The column must be of string type.\nversioned_docs/version-0.16/user-guide/logs/pipeline-config.md:1020:Specify which field uses the skipping index. This index speeds up the query on high cardinality fields but consumes far less storage for building index files. Refer to the [Transform Example](#transform-example) below for syntax.\nversioned_docs/version-0.16/user-guide/logs/pipeline-config.md:1057: index: skipping\nversioned_docs/version-0.16/user-guide/logs/fulltext-index-config.md:12:GreptimeDB provides full-text indexing capabilities to accelerate text search operations. You can configure full-text index when creating or altering tables, with various options to optimize for different use cases. For a general introduction to different types of indexes in GreptimeDB, including inverted index and skipping index, please refer to the [Data Index](/user-guide/manage-data/data-index) guide.\nversioned_docs/version-0.16/user-guide/concepts/why-greptimedb.md:30:GreptimeDB is written in pure Rust for superior performance and reliability. The powerful and fast query engine is powered by vectorized execution and distributed parallel processing (thanks to [Apache DataFusion](https://datafusion.apache.org/)), and combined with [indexing capabilities](/user-guide/manage-data/data-index.md) such as inverted index, skipping index, and full-text index. GreptimeDB combines smart indexing and Massively Parallel Processing (MPP) to boost pruning and filtering.\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/contributor-guide/datanode/data-persistence-indexing.md:40:索引文件采用 [Puffin][3] 格式，这种格式具有较大的灵活性，能够存储更多的元数据，并支持更多的索引结构。\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/contributor-guide/datanode/data-persistence-indexing.md:42:![Puffin](/puffin.png)\nversioned_docs/version-0.16/user-guide/traces/data-model.md:180:We include [skipping\nversioned_docs/version-0.16/user-guide/traces/data-model.md:181:index](/user-guide/manage-data/data-index.md#skipping-index) on `service_name`\nversioned_docs/version-0.16/user-guide/manage-data/data-index.md:2:keywords: [index, inverted index, skipping index, fulltext index, query performance]\nversioned_docs/version-0.16/user-guide/manage-data/data-index.md:3:description: Learn about different types of indexes in GreptimeDB, including inverted index, skipping index, and fulltext index, and how to use them effectively to optimize query performance.\nversioned_docs/version-0.16/user-guide/manage-data/data-index.md:42:However, when you have a large number of unique tag values (Cartesian product among all columns indexed by inverted index), the inverted index may not be the best choice due to the overhead of maintaining the index. It may bring high memory consumption and large index size. In this case, you may consider using the skipping index.\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/user-guide/logs/pipeline-config.md:1018:- `skipping`: 用于指定某列使用 skipping 类型的索引（跳数索引），该列需要是字符串类型\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/user-guide/logs/pipeline-config.md:1039:通过 `index: skipping` 指定在哪个列上建立跳数索引，该索引只需少量存储空间的索引文件即可以加速在高基数列上的查询，写法请参考下方的 [Transform 示例](#transform-示例)。\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/user-guide/logs/pipeline-config.md:1076: index: skipping\nversioned_docs/version-0.16/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\nversioned_docs/version-0.16/user-guide/overview.md:62:Indexes such as inverted indexes, skipping indexes, and full-text indexes can significantly enhance query performance.\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/user-guide/traces/data-model.md:172:引](/user-guide/manage-data/data-index.md#skipping-index)，满足常见的查询场景。\nversioned_docs/version-0.16/user-guide/ingest-data/for-observability/prometheus.md:312:### Enable skipping index\nversioned_docs/version-0.16/user-guide/ingest-data/for-observability/prometheus.md:314:By default, the metric engine won't create indexes for columns. You can enable it by setting the `index.type` to `skipping`.\nversioned_docs/version-0.16/user-guide/ingest-data/for-observability/prometheus.md:316:Create a physical table with a skipping index; all automatically added columns will have this index applied.\nversioned_docs/version-0.16/user-guide/ingest-data/for-observability/prometheus.md:327: \"index.type\" = \"skipping\"\nversioned_docs/version-0.16/user-guide/migrate-to-greptimedb/migrate-from-clickhouse.md:71:> The choice of primary key and the granularity of the time index should be carefully planned based on your business's data volume and query scenarios. If the host cardinality is high (e.g., hundreds of thousands of monitored hosts), you should remove it from the primary key and consider creating a skipping index for it.\ni18n/zh/docusaurus-plugin-content-docs/version-0.16/user-guide/python-scripts/api.md:75:| `limit(skip: int, fetch: Optional[int])` |Limit the number of rows returned from this DataFrame. `skip` - Number of rows to skip before fetch any row; `fetch` - Maximum number of rows to fetch, after skipping skip rows.\nversioned_docs/version-0.16/user-guide/deployments-administration/performance-tuning/design-table.md:2:keywords: [table schema, data model, cardinality, tag columns, field columns, time index, primary key, inverted index, full-text index, skipping index, append-only tables, data updating, wide table, distributed tables, partitioning]\nversioned_docs/version-0.16/user-guide/deployments-administration/performance-tuning/design-table.md:180:For high cardinality columns like `trace_id`, `request_id`, using a [skipping index](/user-guide/manage-data/data-index.md#skipping-index) is more appropriate.\nversioned_docs/version-0.16/user-guide/deployments-administration/performance-tuning/design-table.md:200:The following query can use the skipping index to filter the `request_id` column.\nversioned_docs/version-0.16/user-guide/deployments-administration/performance-tuning/design-table.md:206:However, note that the query capabilities of the skipping index are generally inferior to those of the inverted index.\nversioned_docs/version-0.16/user-guide/deployments-administration/manage-data/compaction.md:23:![SST layout](/compaction-sst-file-layout.jpg)\nversioned_docs/version-0.16/user-guide/deployments-administration/manage-data/region-failover.md:47:

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

(图 1：恢复 Region 3 需要读取比实际大小大 7 倍的冗余数据)

(Figure1: recovery Region 3 need to read redundant data 7 times larger than the actual size)

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'!build'",{"_956":2645,"_937":938,"_958":944},{"_1012":2646,"_986":2634,"_41":-5,"_365":1014,"_1015":-5,"_91":1016},"{\"cmd\": \"pwd && rg --files -g 'AGENTS.md' -g '!node_modules' -g '!build'\"}",{"_956":2648,"_937":938,"_958":944},{"_959":2649,"_961":-5,"_41":-5,"_962":2650,"_95":92,"_91":964},[2651],"commentary",{"_45":2652,"_91":967},"I’ll update the docs requested in the PR follow-up and verify the MDX style-prop issue against the relevant versioned/localized copies.",{"_956":2654,"_937":938,"_958":944},{"_41":2655,"_962":2650,"_45":2652,"_91":972},"msg_0007f01cb86e35e4016a27a2ff21388197b4a1eb5bd6d82099",{"_956":2657,"_937":938,"_958":944},{"_2658":2659,"_41":-5,"_949":112,"_91":2660},"action",{"_2661":2662,"_1847":2663,"_91":1849},"web_search_call","queries",[2663],"Docusaurus 3 MDX img style prop React object style string build error",{"_956":2665,"_937":938,"_958":944},{"_2658":2666,"_41":2667,"_1847":2663,"_91":2668},{"_2661":2669,"_1847":2663,"_91":1849},"ws_0007f01cb86e35e4016a27a2fa25dc8197831b4d94507178ab","webSearch",[2663],{"_956":2671,"_937":938,"_958":944},{"_959":-5,"_975":-5,"_41":-5,"_976":2672,"_91":978},[],{"_956":2674,"_937":938,"_958":944},{"_959":2675,"_41":2676,"_976":2677,"_91":978},[],"rs_0007f01cb86e35e4016a27a2f9014c8197835bd967a398e116",[],{"_956":2679,"_937":938,"_958":944},{"_959":2680,"_41":2681,"_91":2682},[2683],"710fa42f-c30c-489d-870d-4b33ab7501ba","userMessage",{"_45":2684,"_2685":2686,"_91":45},"\nYou are Codex, assisting with follow-up actions on a GitHub pull request.\n\nInput blocks\n------------\n… # The comment or event that invoked you\n… # PR metadata (title, branches, SHAs, status, etc.)\n… # Comments / Reviews for the PR\n\nPossible triggers\n• A user mentions you (@codex)\n• A reviewer requests changes\n• An automated or internal system asks you to review / update\n\nGuidelines\n1. Read the block first and treat it as the primary intent.\n2. Always consult and to interpret and validate the trigger; use only context that materially affects your decision and ignore the rest.\n3. If the trigger comes from a comment thread, the first block will be combined earlier comments from the same thread, clearly indicated with `Comments in the same thread`.\n4. Remaining blocks are in chronological order, oldest first, one block per comment.\n5. When the trigger relates to CI/build status (e.g., “help me fix CI”), incorporate CI/status details found in as supporting context.\n6. If code change is needed, generate a **new** PR with the requested changes. The PR title and message should summarize the changes **on top** of the original pull request.\n@codex update zh docs and version 1.0 docs.{\"title\":\"docs: document how data is organized in SST files\",\"body\":\"## What's Changed in this PR\\r\\n\\r\\n\\r\\nExplain the physical SST layout in the storage engine docs:\\r\\n\\r\\n- storage-engine.md: add Data Layout in SST Files (sort order, internal\\r\\n columns, row groups, file metadata) and Scan Pruning sections with\\r\\n diagrams; touch up the WAL/SST/Compactor bullets.\\r\\n- data-persistence-indexing.md: note skipping and full-text indexes are\\r\\n also stored in Puffin files.\\r\\n- data-model.md and design-table.md: cross-link to the storage engine doc\\r\\n for how data is laid out in SST files.\\r\\n\\r\\n\\r\\n## Checklist\\r\\n\\r\\n- [x] Please confirm that all corresponding versions of the documents have been revised.\\r\\n- [x] Please ensure that the content in `sidebars.ts` matches the current document structure when you changed the document structure.\\r\\n- [ ] This change requires follow-up update in localized docs.\\r\\n\",\"base_ref\":\"bd7473872de0cc659884870c3c1a5f9ea7cc9bc9\",\"head_ref\":\"74147ec8b76a76d7307941840cecb60a0ad40049\",\"merge_commit_sha\":null,\"type\":\"pull_request_info\"}{\"type\":\"pull_request_comment\",\"body\":\"Will sync the versioned docs and zh docs later.\",\"path\":\"docs/contributor-guide/datanode/data-persistence-indexing.md\",\"side\":\"RIGHT\",\"line\":1}{\"type\":\"pull_request_comment\",\"body\":\"## Deploying greptime-docs with $\\\"Cloudflare$ Cloudflare Pages\\n\\n\\n\\n\\n\\n

Latest commit:	\\n`74147ec`\\n
Status:	✅ Deploy successful!
Preview URL:	\\nhttps://e5338d83.greptime-docs.pages.dev\\n
Branch Preview URL:	\\nhttps://docs-sst-data-layout.greptime-docs.pages.dev\\n

\\n\\n[View logs](https://dash.cloudflare.com/?to=/baee2593068c89990bf86c4ea1c28258/pages/view/greptime-docs/e5338d83-afae-4eff-9397-006c853807a2)\\n\",\"path\":null,\"side\":null,\"line\":null}{\"type\":\"pull_request_comment\",\"body\":\"\\n### 💡 Codex Review\\n\\nHere are some automated review suggestions for this pull request.\\n\\n**Reviewed commit:** `83ff57a1f4`\\n \\n\\n

ℹ️ About Codex in GitHub

\\n
\\n\\n[Your team has set up Codex to review pull requests in this repo](https://chatgpt.com/codex/cloud/settings/general). Reviews are triggered when you\\n- Open a pull request for review\\n- Mark a draft as ready\\n- Comment \\\"@codex review\\\".\\n\\nIf Codex has suggestions, it will comment; otherwise it will react with 👍.\\n\\n\\n\\n\\nCodex can also answer questions or update the PR. Try commenting \\\"@codex address that feedback\\\".\\n \\n

\",\"path\":null,\"side\":null,\"line\":null}{\"type\":\"pull_request_comment\",\"body\":\"**_{_{![P1 Badge](https://img.shields.io/badge/P1-orange?style=flat)}} Fix MDX style props to keep docs build working**\\n\\nIn this Docusaurus 3/MDX page, the `` tag is compiled as JSX and the `style` attribute is passed to React; a string value makes React SSR throw because `style` must be an object, so building this doc page will fail when it renders the new image. The same string-style pattern is used for the scan-pruning image below, so use a class or an object style such as `style={{ width: '80%', margin: '0 auto' }}` for both images.\\n\\nUseful? React with 👍 / 👎.\",\"path\":\"docs/contributor-guide/datanode/storage-engine.md\",\"side\":\"RIGHT\",\"line\":null}{\"type\":\"pull_request_comment\",\"body\":\"LGTM\",\"path\":null,\"side\":null,\"line\":null}","text_elements",[],{"_956":2688,"_937":938,"_958":944},{"_959":2689,"_961":-5,"_41":-5,"_962":-5,"_95":505,"_91":964},[2690],{"_45":2684,"_91":2691},"input_text",{"_956":2693,"_937":938,"_958":944},{"_959":2694,"_961":-5,"_41":-5,"_962":-5,"_95":505,"_91":964},[2695],{"_45":2696,"_91":2691},"\n /workspace/docs\n bash\n 2026-06-09\n Etc/UTC\n",{"_956":2698,"_937":938,"_958":944},{"_959":2699,"_961":-5,"_41":-5,"_962":-5,"_95":2700,"_91":964},[2701,2702],"developer",{"_45":2704,"_91":2691},{"_45":2703,"_91":2691},"\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- imagegen: Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas. (file: /opt/codex/skills/.system/imagegen/SKILL.md)\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /opt/codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /opt/codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /opt/codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /opt/codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.\n","\nFilesystem sandboxing defines which files can be read or written. `sandbox_mode` is `danger-full-access`: No filesystem sandboxing - all commands are permitted. Network access is enabled.\nApproval policy is currently never. Do not provide the `sandbox_permissions` for any reason, commands will be rejected.\n","turn/started",{"_937":938,"_86":2707},{"_102":-5,"_41":944,"_945":2708,"_947":948,"_949":2709},[],"inProgress",{"_949":2711,"_937":938},{"_2712":2713,"_91":2714},"activeFlags",[],"active","thread/started",{"_2717":2718},"thread",{"_2719":-5,"_2720":-5,"_2721":2722,"_2723":948,"_999":1000,"_2724":15,"_2725":-5,"_2726":-5,"_41":938,"_2727":2728,"_365":-5,"_254":2729,"_2730":379,"_1004":2731,"_949":2732,"_76":2733,"_2734":948},"agentNickname","agentRole","cliVersion","0.124.0","createdAt","ephemeral","forkedFromId","gitInfo","modelProvider","openai","/opt/codex/sessions/2026/06/09/rollout-2026-06-09T05-21-56-019eaad4-89db-7083-bcf4-b92dc45085b3.jsonl","preview","vscode",{"_91":953},[],"updatedAt",[],"messages",[2738],{"_41":2739,"_2740":2741,"_2742":2743,"_2744":2743,"_959":2745,"_949":2746,"_961":-5,"_2747":31,"_2748":2749,"_2750":2751,"_2752":-5},"402dd515-d860-4837-b7b1-806d34c704b6","author",{"_95":505,"_365":-5,"_2748":2761},"create_time",1780982515.467923,"update_time",{"_2757":45,"_2758":2759},"finished_successfully","weight","metadata",{"_2753":2754},"recipient","all","channel","l1239dk1",{"_2755":2756},"inline_comments",[],"content_type","parts",[2760],"@codex update zh docs and version 1.0 docs.\ndocs: document how data is organized in SST files\n\n## What's Changed in this PR\r\n\r\n\r\nExplain the physical SST layout in the storage engine docs:\r\n\r\n- storage-engine.md: add Data Layout in SST Files (sort order, internal\r\n columns, row groups, file metadata) and Scan Pruning sections with\r\n diagrams; touch up the WAL/SST/Compactor bullets.\r\n- data-persistence-indexing.md: note skipping and full-text indexes are\r\n also stored in Puffin files.\r\n- data-model.md and design-table.md: cross-link to the storage engine doc\r\n for how data is laid out in SST files.\r\n\r\n\r\n## Checklist\r\n\r\n- [x] Please confirm that all corresponding versions of the documents have been revised.\r\n- [x] Please ensure that the content in `sidebars.ts` matches the current document structure when you changed the document structure.\r\n- [ ] This change requires follow-up update in localized docs.\r\n\nWill sync the versioned docs and zh docs later.\n## Deploying greptime-docs with $\"Cloudflare$ Cloudflare Pages\n\n\n\n\n\n

Latest commit:	\n`74147ec`\n
Status:	✅ Deploy successful!
Preview URL:	\nhttps://e5338d83.greptime-docs.pages.dev\n
Branch Preview URL:	\nhttps://docs-sst-data-layout.greptime-docs.pages.dev\n

\n\n[View logs](https://dash.cloudflare.com/?to=/baee2593068c89990bf86c4ea1c28258/pages/view/greptime-docs/e5338d83-afae-4eff-9397-006c853807a2)\n\n\n### 💡 Codex Review\n\nHere are some automated review suggestions for this pull request.\n\n**Reviewed commit:** `83ff57a1f4`\n \n\n

ℹ️ About Codex in GitHub

\n
\n\n[Your team has set up Codex to review pull requests in this repo](https://chatgpt.com/codex/cloud/settings/general). Reviews are triggered when you\n- Open a pull request for review\n- Mark a draft as ready\n- Comment \"@codex review\".\n\nIf Codex has suggestions, it will comment; otherwise it will react with 👍.\n\n\n\n\nCodex can also answer questions or update the PR. Try commenting \"@codex address that feedback\".\n \n

\n**_{_{![P1 Badge](https://img.shields.io/badge/P1-orange?style=flat)}} Fix MDX style props to keep docs build working**\n\nIn this Docusaurus 3/MDX page, the `` tag is compiled as JSX and the `style` attribute is passed to React; a string value makes React SSR throw because `style` must be an object, so building this doc page will fail when it renders the new image. The same string-style pattern is used for the scan-pruning image below, so use a class or an object style such as `style={{ width: '80%', margin: '0 auto' }}` for both images.\n\nUseful? React with 👍 / 👎.\nLGTM",{},"created",1780983448.0572212,"Completing the task","event_type","info",{"_91":964,"_95":92,"_959":2797},{"_91":2794,"_2795":2796},{"_91":2770,"_2771":2772,"_2773":2774,"_2775":2776,"_2777":-5},"pr","pr_title","docs: sync SST file layout & scan-pruning to v1.0 and zh; fix MDX image style","pr_message","### Motivation\n\n- Ensure the new explanation of how data is organized in SST files is present in the versioned `v1.0` docs and Chinese localized copies so readers of all versions/locales see the same guidance. \n- Clarify that multiple index types (inverted, skipping, full-text) are stored in Puffin index files. \n- Prevent MDX/React SSR build errors by using JSX object-style `style` props for images instead of string-style attributes.\n\n### Description\n\n- Added the `Data Layout in SST Files` and `Scan Pruning` sections to `storage-engine.md` in `docs`, `versioned_docs/version-1.0`, and the corresponding `i18n/zh` files, including example layout, internal columns (`__primary_key`, `__sequence`, `__op_type`), row-group/file metadata, and SST format notes. \n- Updated `data-persistence-indexing.md` (current and v1.0, plus zh) to state that GreptimeDB stores inverted, skipping (bloom-filter-backed), and full-text indexes as Blobs inside Puffin files. \n- Added cross-links from `concepts/data-model.md` and `performance-tuning/design-table.md` (current and v1.0, plus zh) to the storage engine's SST layout section. \n- Replaced string `style` attributes on MDX `` tags with JSX object-style `style={{ width: '80%', margin: '0 auto' }}` in the updated pages so React SSR does not throw. \n- Changes applied to both English `docs`/`versioned_docs/version-1.0` and Chinese `i18n/zh/docusaurus-plugin-content-docs` directories to keep current and versioned localized docs in sync.\n\n### Testing\n\n- Ran `pnpm install --frozen-lockfile` and the install completed successfully. \n- Built the site with `pnpm build`; the build completed successfully and produced the static site (`[SUCCESS] Generated static files in \"build\"`) after temporarily moving interfering untracked Yarn PnP files out of the repo root and restoring them. \n- Ran `git diff --check -- docs versioned_docs/version-1.0 i18n/zh/docusaurus-plugin-content-docs/current i18n/zh/docusaurus-plugin-content-docs/version-1.0` and it returned no check errors. \n- The build emitted non-fatal warnings about a few unsupported/DrawIO SVG variants, but these did not cause the build to fail.","output_diff",{"_91":2775,"_2778":376,"_127":128,"_2779":-5,"_504":2780,"_2781":2782,"_2783":2784,"_2785":2786,"_2787":2784,"_2788":1132,"_2789":2790},"pre_apply_patch","repo_id","preapply_patch_base_commit_sha","diff --git a/i18n/zh/docusaurus-plugin-content-docs/current/contributor-guide/datanode/data-persistence-indexing.md b/i18n/zh/docusaurus-plugin-content-docs/current/contributor-guide/datanode/data-persistence-indexing.md\nindex 65f3b04ec2feb0b056caf778a22983b74805dcd1..6fae06e243fcf52daccd45f618e7c5790ba6219a 100644\n--- a/i18n/zh/docusaurus-plugin-content-docs/current/contributor-guide/datanode/data-persistence-indexing.md\n+++ b/i18n/zh/docusaurus-plugin-content-docs/current/contributor-guide/datanode/data-persistence-indexing.md\n@@ -19,51 +19,51 @@ Parquet 具有层次结构，类似于“行组 - 列-数据页”。Parquet 文\n \n $\"Parquet$ \n \n ## 数据持久化\n \n GreptimeDB 提供了 `storage.flush.global_write_buffer_size` 的配置项来设置全局的 Memtable 大小阈值。当数据库所有 MemTable 中的数据量之和达到阈值时将自动触发持久化操作，将 MemTable 的数据 flush 到 SST 文件中。\n \n \n ## SST 文件中的索引数据\n \n Apache Parquet 文件格式在列块和数据页的头部提供了内置的统计信息，用于剪枝和跳过。\n \n $\"Column$ \n \n 例如，在上述 Parquet 文件中，如果你想要过滤 `name` 等于 `Emily` 的行，你可以轻松跳过行组 0，因为 `name` 字段的最大值是 `Charlie`。这些统计信息减少了 IO 操作。\n \n \n ## 索引文件\n \n 对于每个 SST 文件，GreptimeDB 不但维护 SST 文件内部索引，还会单独生成一个文件用于存储针对该 SST 文件的索引结构。\n \n 索引文件采用 [Puffin][3] 格式，这种格式具有较大的灵活性，能够存储更多的元数据，并支持更多的索引结构。\n \n ![Puffin](/puffin.png)\n \n-目前，倒排索引是 GreptimeDB 第一个支持的单独索引结构，以 Blob 的形式存储在索引文件中。\n+GreptimeDB 会将多种索引结构作为 Blob 存储在 Puffin 文件中，包括倒排索引、跳数索引（基于 bloom filter）和全文索引。倒排索引是最早支持的索引结构，下面将详细介绍。\n \n \n ## 倒排索引\n \n 在 v0.7 版本中，GreptimeDB 引入了倒排索引（Inverted Index）来加速查询。\n \n 倒排索引是一种常见的用于全文搜索的索引结构，它将文档中的每个单词映射到包含该单词的文档列表，GreptimeDB 把这项源自于搜索引擎的技术应用到了时间序列数据库中。\n \n 搜索引擎和时间序列数据库虽然运行在不同的领域，但是应用的倒排索引技术背后的原理是相似的。这种相似性需要一些概念上的调整：\n 1. 单词：在 GreptimeDB 中，指时间线的列值。\n 2. 文档：在 GreptimeDB 中，指包含多个时间线的数据段。\n \n 倒排索引的引入，使得 GreptimeDB 可以跳过不符合查询条件的数据段，从而提高扫描效率。\n \n ![Inverted index searching](/inverted-index-searching.png)\n \n 例如，上述查询使用倒排索引来定位数据段，数据段满足条件：`job` 等于 `apiserver`，`handler` 符合正则匹配 `.*users` 及 `status` 符合正则匹配 `4..`，然后扫描这些数据段以产生满足所有条件的最终结果，从而显着减少 IO 操作的次数。\n \n ### 倒排索引格式\n \n ![Inverted index format](/inverted-index-format.png)\n \n GreptimeDB 按列构建倒排索引，每个倒排索引包含一个 FST 和多个 Bitmap。\n \n FST（Finite State Transducer）允许 GreptimeDB 以紧凑的格式存储列值到 Bitmap 位置的映射，并且提供了优秀的搜索性能和支持复杂搜索（例如正则表达式匹配）；Bitmap 则维护了数据段 ID 列表，每个位表示一个数据段。\ndiff --git a/i18n/zh/docusaurus-plugin-content-docs/current/contributor-guide/datanode/storage-engine.md b/i18n/zh/docusaurus-plugin-content-docs/current/contributor-guide/datanode/storage-engine.md\nindex 6a55d2cb2f4ec615f2cba96e1f6a8efee232cf7e..1111c14463f2c7539bd8d37e1ab1cec0d7d888bd 100644\n--- a/i18n/zh/docusaurus-plugin-content-docs/current/contributor-guide/datanode/storage-engine.md\n+++ b/i18n/zh/docusaurus-plugin-content-docs/current/contributor-guide/datanode/storage-engine.md\n@@ -1,62 +1,113 @@\n ---\n keywords: [存储引擎, Mito, LSMT, 数据模型, Region]\n description: 详细介绍了 GreptimeDB 的存储引擎架构、数据模型和 region 的概念，重点描述了 Mito 存储引擎的优化和组件。\n ---\n \n # 存储引擎\n \n ## 概述\n \n `存储引擎` 负责存储数据库的数据。Mito 是我们默认使用的存储引擎，基于 [LSMT][1]（Log-structured Merge-tree）。我们针对处理时间序列数据的场景做了很多优化，因此 mito 这个存储引擎并不适用于通用用途。\n \n ## 架构\n 下图展示了存储引擎的架构和处理数据的流程。\n \n ![Architecture](/storage-engine-arch.png)\n \n 该架构与传统的 LSMT 引擎相同：\n \n - [WAL][2]\n - 为尚未刷盘的数据提供高持久性保证。\n - 基于 `LogStore` API 实现，不关心底层存储介质。\n- - WAL 的日志记录可以存储在本地磁盘上，也可以存储在实现了 `LogStore` API 的分布式日志服务中。\n+ - WAL 的日志记录可以存储在本地磁盘上，也可以存储在实现了 `LogStore` API 的远程日志服务中，例如 Kafka（remote WAL）。\n - Memtable\n - 数据首先写入 `active memtable`，又称 `mutable memtable`。\n - 当 `mutable memtable` 已满时，它将变为只读的 `immutable memtable`。\n - SST\n - SST 的全名为有序字符串表（`Sorted String Table`）。\n - `immutable memtable` 刷到持久存储后形成一个 SST 文件。\n+ - SST 中的行按照主键和时间索引排序；详见 [SST 文件中的数据布局](#sst-文件中的数据布局)。\n - Compactor\n - `Compactor` 通过 compaction 操作将小的 SST 合并为大的 SST。\n- - 默认使用 [TWCS][3] 策略进行合并\n+ - 默认使用 [TWCS][3] 策略进行合并。Compaction 会按照时间窗口组织 SST 文件，并结合 TTL 清理过期数据。详见 [Compaction](/user-guide/deployments-administration/manage-data/compaction.md)。\n - Manifest\n - `Manifest` 存储引擎的元数据，例如 SST 的元数据。\n - Cache\n - 加速查询操作。\n \n [1]: https://en.wikipedia.org/wiki/Log-structured_merge-tree\n [2]: https://en.wikipedia.org/wiki/Write-ahead_logging\n [3]: https://cassandra.apache.org/doc/latest/cassandra/operating/compaction/twcs.html\n \n ## 数据模型\n \n 存储引擎提供的数据模型介于 `key-value` 模型和表模型之间\n \n ```txt\n tag-1, ..., tag-m, timestamp -> field-1, ..., field-n\n ```\n \n 每一行数据包含多个 tag 列，一个 timestamp 列和多个 field 列\n - `0 ~ m` 个 tag 列\n - tag 列是可空的\n - 在建表时通过 `PRIMARY KEY` 指定\n - 必须包含一个 timestamp 列\n - timestamp 列非空\n - 在建表时通过 `TIME INDEX` 指定\n - `0 ~ n` 个 field 列\n - field 列是可空的\n - 数据按照 tag 列和 timestamp 列有序存储\n \n ## Region\n \n 数据在存储引擎中以 `region` 的形式存储，`region` 是引擎中的一个逻辑隔离存储单元。`region` 中的行必须具有相同的 `schema`（模式），该 `schema` 定义了 `region` 中的 tag 列，timestamp 列和 field 列。数据库中表的数据存储在一到多个 `region` 中。\n+\n+## SST 文件中的数据布局\n+\n+当 memtable 被 flush 时，Mito 会把其中的行写入不可变的 [Apache Parquet](https://parquet.apache.org) SST 文件。关于 Parquet 文件格式本身以及 SST 文件如何建立索引，详见[数据持久化和索引](data-persistence-indexing.md)。\n+\n+在一个 SST 文件内，行按照 `(primary key, time index)` 排序。具有相同 primary key（tag 列）的行属于同一条时间序列，会连续存储并按时间戳排序。这种局部性使得扫描单条时间序列的成本更低，也有助于提升压缩效果。对于没有 primary key 的 append-only 表，行仅按 time index 排序。\n+\n+例如，考虑一个存储主机指标的表：\n+\n+```sql\n+CREATE TABLE host_metrics (\n+ host STRING,\n+ region STRING,\n+ ts TIMESTAMP TIME INDEX,\n+ cpu DOUBLE,\n+ memory DOUBLE,\n+ PRIMARY KEY (host, region)\n+);\n+```\n+\n+Mito 会按 primary key 对行分组，并按时间排序，因此 SST 中的数据在概念上类似于：\n+\n+| host | region | ts | cpu | memory |\n+| --- | --- | --- | --- | --- |\n+| host-a | us-east | 10:00 | 0.42 | 7.1 |\n+| host-a | us-east | 10:01 | 0.47 | 7.4 |\n+| host-a | us-west | 10:00 | 0.31 | 6.8 |\n+| host-b | us-east | 10:00 | 0.80 | 8.6 |\n+\n+除了表中的列，Mito 还会在每个 SST 文件中存储三个内部列，以便在从多个 memtable 和 SST 文件读取时正确地合并、去重并应用删除操作：\n+\n+- `__primary_key`：行的编码后 primary key（tags）。\n+- `__sequence`：行的 sequence number。\n+- `__op_type`：行的操作类型（put 或 delete）。\n+\n+每个 Parquet SST 都会被切分为 row group，row group 是 Parquet 可以独立读取或跳过的单位。每个 row group 都带有列统计信息，例如最小值、最大值和 null 数量。Mito 还会为每个 SST 记录文件级元数据，包括时间范围、行数、row group 数量、可用索引以及 primary key 范围。这些统计信息会驱动下面介绍的扫描裁剪。\n+\n+Mito 支持两种 SST 格式：`flat`（默认）和 `primary_key`。它们以不同方式编码 primary key，并针对不同的 primary key 基数进行优化。如何选择两种格式，详见 [SST format](/reference/sql/create.md#创建指定-sst-格式的表) 和[表设计指南](/user-guide/deployments-administration/performance-tuning/design-table.md#选择合适的-sst-格式)。\n+\n+ $\"SST$ \n+\n+## 扫描裁剪\n+\n+Mito 会组合多个从粗到细的裁剪步骤，避免读取不可能匹配查询的数据：\n+\n+1. **时间范围裁剪。** 如果文件和 memtable 的时间范围与查询时间范围不相交，就会在打开 reader 之前被跳过。对于时间序列查询，这通常是成本最低且最有效的步骤。\n+2. **Row group 统计信息。** 如果 row group 的 min-max 统计信息能够证明没有任何行匹配谓词，则会跳过整个 row group。\n+3. **索引。** 倒排索引、跳数索引和全文索引可以针对统计信息无法处理的谓词提供更精细的裁剪。详见[数据持久化和索引](data-persistence-indexing.md)。\n+\n+ $\"Scan$ \ndiff --git a/i18n/zh/docusaurus-plugin-content-docs/current/user-guide/concepts/data-model.md b/i18n/zh/docusaurus-plugin-content-docs/current/user-guide/concepts/data-model.md\nindex 035f9268a4d268efe843534c9eb0afdbc189d1fa..2e7eb8f8a977422d3c087bb3019c164eead54e6d 100644\n--- a/i18n/zh/docusaurus-plugin-content-docs/current/user-guide/concepts/data-model.md\n+++ b/i18n/zh/docusaurus-plugin-content-docs/current/user-guide/concepts/data-model.md\n@@ -1,44 +1,44 @@\n ---\n keywords: [数据模型, 表结构, 列类型, 设计考虑, 时序表, Tag, Timestamp, Field, Metrics, Logs, Traces]\n description: 介绍 GreptimeDB 的数据模型，包括表结构、列类型和设计考虑，适用于 metrics、logs 和 traces 数据。\n ---\n \n # 数据模型\n \n ## 模型\n \n GreptimeDB 使用时序表来组织、压缩和管理数据的过期。数据模型基于关系型数据库的表模型，同时针对 metrics、logs、traces 的特点做了适配。\n \n 所有数据按表组织，每个表中的列分为三种语义类型：`Tag`、`Timestamp` 和 `Field`。\n \n - 表名通常和指标名、日志源名或 metric 名称一致。\n - `Tag` 列标识时间序列的身份。相同 Tag 值的行属于同一条时间序列（有些 TSDB 也叫 label）。\n - `Timestamp` 是时序数据库的根基，表示数据的生成时间。每个表只能有一个 `Timestamp` 类型的列，也叫时间索引（`Time Index`）。\n - 其余列是 `Field` 列，存放实际的数据指标或日志内容，通常是数值或字符串，也可以是地理位置、时间戳等其他类型。\n \n-表按时间序列组织行，同一时间序列内按 `Timestamp` 排序。表还可以对相同 `Tag` + `Timestamp` 的行做去重，具体取决于业务需求。选择合适的表结构对查询和存储效率至关重要，详见[表设计指南](/user-guide/deployments-administration/performance-tuning/design-table.md)。\n+表按时间序列组织行，同一时间序列内按 `Timestamp` 排序。表还可以对相同 `Tag` + `Timestamp` 的行做去重，具体取决于业务需求。物理上，GreptimeDB 会把数据持久化为不可变的 Parquet SST 文件，行按照 `(primary key, timestamp)` 排序；当表没有 primary key（例如下面的 append-only 日志表）时，仅按照 timestamp 排序。要了解 SST 文件中的数据布局和裁剪方式，详见[存储引擎](/contributor-guide/datanode/storage-engine.md#sst-文件中的数据布局)文档。选择合适的表结构对查询和存储效率至关重要，详见[表设计指南](/user-guide/deployments-administration/performance-tuning/design-table.md)。\n \n ### Metrics\n \n 假设有一个 `system_metrics` 表，监控数据中心机器的资源使用：\n \n ```sql\n CREATE TABLE IF NOT EXISTS system_metrics (\n host STRING,\n idc STRING,\n cpu_util DOUBLE,\n memory_util DOUBLE,\n disk_util DOUBLE,\n ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,\n PRIMARY KEY(host, idc),\n TIME INDEX(ts)\n );\n ```\n \n 数据模型如下：\n \n ![time-series-table-model](/time-series-data-model.svg)\n \n 和常见的关系表模型很像，区别在于 `TIME INDEX` 约束——用来指定 `ts` 列为时间索引。\n \n - 表名 `system_metrics`。\ndiff --git a/i18n/zh/docusaurus-plugin-content-docs/current/user-guide/deployments-administration/performance-tuning/design-table.md b/i18n/zh/docusaurus-plugin-content-docs/current/user-guide/deployments-administration/performance-tuning/design-table.md\nindex 346ba366053ad6eb57f30593e504e457d22cda60..6be519f03d168c7201df2277b46c662cd1272647 100644\n--- a/i18n/zh/docusaurus-plugin-content-docs/current/user-guide/deployments-administration/performance-tuning/design-table.md\n+++ b/i18n/zh/docusaurus-plugin-content-docs/current/user-guide/deployments-administration/performance-tuning/design-table.md\n@@ -23,50 +23,53 @@ description: 详细介绍了 GreptimeDB 的数据模型使用指南，以及常\n 例如，`namespace`、`cluster`、`http_method` 通常是低基数的。\n - **高基数（High Cardinality）**：高基数列包含大量的唯一值。\n 例如，`trace_id`、`span_id`、`user_id`、`uri`、`ip`、`uuid`、`request_id`、表的自增 ID，时间戳通常是高基数的。\n \n \n ## 列类型\n \n 在 GreptimeDB 中，列被分为三种语义类型：`Tag`、`Field` 和 `Timestamp`。\n 时间戳通常表示数据采样的时间或日志/事件发生的时间。\n GreptimeDB 使用 `TIME INDEX` 约束来标识 `Timestamp` 列。\n 因此，`Timestamp` 列也被称为 `TIME INDEX` 列。\n 如果你有多个时间戳数据类型的列，你只能将其中一个定义为 `TIME INDEX`，其他的定义为 `Field` 列。\n \n 在 GreptimeDB 中，Tag 列是可选的。Tag 列的主要用途包括：\n \n 1. 定义存储时数据的排序方式。\n GreptimeDB 使用 `PRIMARY KEY` 约束来定义 tag 列和 tag 的排序顺序。\n 与传统数据库不同，GreptimeDB 的主键是用来定义时间序列的。\n GreptimeDB 中的表按照 `(primary key, timestamp)` 的顺序对行进行排序。\n 这提高了具有相同 tag 数据的局部性。\n 如果没有定义 tag 列，GreptimeDB 按时间戳对行进行排序。\n 2. 唯一标识一个时间序列。\n 当表不是 append-only 模式时，GreptimeDB 根据时间戳在同一时间序列（主键）下去除重复行。\n 3. 便于从使用 label 或 tag 的其他时序数据库迁移。\n \n+这种顺序就是磁盘上 Parquet SST 文件中的物理行布局。\n+要了解数据在 SST 文件中如何组织，以及这种排序、tag 基数和索引为什么会影响性能，详见[存储引擎](/contributor-guide/datanode/storage-engine.md#sst-文件中的数据布局)文档。\n+\n \n ## 主键\n \n ### 主键是可选的\n \n 错误的主键或索引可能会显著降低性能。\n 通常，你可以创建一个没有主键的仅追加表，因为对于许多场景来说，按时间戳排序数据已经有不错测性能了。\n 这也可以作为性能基准。\n \n ```sql\n CREATE TABLE http_logs (\n access_time TIMESTAMP TIME INDEX,\n application STRING,\n remote_addr STRING,\n http_status STRING,\n http_method STRING,\n http_refer STRING,\n user_agent STRING,\n request_id STRING,\n request STRING,\n ) with ('append_mode'='true');\n ```\n \n `http_logs` 表是存储 HTTP 服务器日志的示例。\n \ndiff --git a/i18n/zh/docusaurus-plugin-content-docs/version-1.0/contributor-guide/datanode/data-persistence-indexing.md b/i18n/zh/docusaurus-plugin-content-docs/version-1.0/contributor-guide/datanode/data-persistence-indexing.md\nindex 65f3b04ec2feb0b056caf778a22983b74805dcd1..6fae06e243fcf52daccd45f618e7c5790ba6219a 100644\n--- a/i18n/zh/docusaurus-plugin-content-docs/version-1.0/contributor-guide/datanode/data-persistence-indexing.md\n+++ b/i18n/zh/docusaurus-plugin-content-docs/version-1.0/contributor-guide/datanode/data-persistence-indexing.md\n@@ -19,51 +19,51 @@ Parquet 具有层次结构，类似于“行组 - 列-数据页”。Parquet 文\n \n $\"Parquet$ \n \n ## 数据持久化\n \n GreptimeDB 提供了 `storage.flush.global_write_buffer_size` 的配置项来设置全局的 Memtable 大小阈值。当数据库所有 MemTable 中的数据量之和达到阈值时将自动触发持久化操作，将 MemTable 的数据 flush 到 SST 文件中。\n \n \n ## SST 文件中的索引数据\n \n Apache Parquet 文件格式在列块和数据页的头部提供了内置的统计信息，用于剪枝和跳过。\n \n $\"Column$ \n \n 例如，在上述 Parquet 文件中，如果你想要过滤 `name` 等于 `Emily` 的行，你可以轻松跳过行组 0，因为 `name` 字段的最大值是 `Charlie`。这些统计信息减少了 IO 操作。\n \n \n ## 索引文件\n \n 对于每个 SST 文件，GreptimeDB 不但维护 SST 文件内部索引，还会单独生成一个文件用于存储针对该 SST 文件的索引结构。\n \n 索引文件采用 [Puffin][3] 格式，这种格式具有较大的灵活性，能够存储更多的元数据，并支持更多的索引结构。\n \n ![Puffin](/puffin.png)\n \n-目前，倒排索引是 GreptimeDB 第一个支持的单独索引结构，以 Blob 的形式存储在索引文件中。\n+GreptimeDB 会将多种索引结构作为 Blob 存储在 Puffin 文件中，包括倒排索引、跳数索引（基于 bloom filter）和全文索引。倒排索引是最早支持的索引结构，下面将详细介绍。\n \n \n ## 倒排索引\n \n 在 v0.7 版本中，GreptimeDB 引入了倒排索引（Inverted Index）来加速查询。\n \n 倒排索引是一种常见的用于全文搜索的索引结构，它将文档中的每个单词映射到包含该单词的文档列表，GreptimeDB 把这项源自于搜索引擎的技术应用到了时间序列数据库中。\n \n 搜索引擎和时间序列数据库虽然运行在不同的领域，但是应用的倒排索引技术背后的原理是相似的。这种相似性需要一些概念上的调整：\n 1. 单词：在 GreptimeDB 中，指时间线的列值。\n 2. 文档：在 GreptimeDB 中，指包含多个时间线的数据段。\n \n 倒排索引的引入，使得 GreptimeDB 可以跳过不符合查询条件的数据段，从而提高扫描效率。\n \n ![Inverted index searching](/inverted-index-searching.png)\n \n 例如，上述查询使用倒排索引来定位数据段，数据段满足条件：`job` 等于 `apiserver`，`handler` 符合正则匹配 `.*users` 及 `status` 符合正则匹配 `4..`，然后扫描这些数据段以产生满足所有条件的最终结果，从而显着减少 IO 操作的次数。\n \n ### 倒排索引格式\n \n ![Inverted index format](/inverted-index-format.png)\n \n GreptimeDB 按列构建倒排索引，每个倒排索引包含一个 FST 和多个 Bitmap。\n \n FST（Finite State Transducer）允许 GreptimeDB 以紧凑的格式存储列值到 Bitmap 位置的映射，并且提供了优秀的搜索性能和支持复杂搜索（例如正则表达式匹配）；Bitmap 则维护了数据段 ID 列表，每个位表示一个数据段。\ndiff --git a/i18n/zh/docusaurus-plugin-content-docs/version-1.0/contributor-guide/datanode/storage-engine.md b/i18n/zh/docusaurus-plugin-content-docs/version-1.0/contributor-guide/datanode/storage-engine.md\nindex 6a55d2cb2f4ec615f2cba96e1f6a8efee232cf7e..1111c14463f2c7539bd8d37e1ab1cec0d7d888bd 100644\n--- a/i18n/zh/docusaurus-plugin-content-docs/version-1.0/contributor-guide/datanode/storage-engine.md\n+++ b/i18n/zh/docusaurus-plugin-content-docs/version-1.0/contributor-guide/datanode/storage-engine.md\n@@ -1,62 +1,113 @@\n ---\n keywords: [存储引擎, Mito, LSMT, 数据模型, Region]\n description: 详细介绍了 GreptimeDB 的存储引擎架构、数据模型和 region 的概念，重点描述了 Mito 存储引擎的优化和组件。\n ---\n \n # 存储引擎\n \n ## 概述\n \n `存储引擎` 负责存储数据库的数据。Mito 是我们默认使用的存储引擎，基于 [LSMT][1]（Log-structured Merge-tree）。我们针对处理时间序列数据的场景做了很多优化，因此 mito 这个存储引擎并不适用于通用用途。\n \n ## 架构\n 下图展示了存储引擎的架构和处理数据的流程。\n \n ![Architecture](/storage-engine-arch.png)\n \n 该架构与传统的 LSMT 引擎相同：\n \n - [WAL][2]\n - 为尚未刷盘的数据提供高持久性保证。\n - 基于 `LogStore` API 实现，不关心底层存储介质。\n- - WAL 的日志记录可以存储在本地磁盘上，也可以存储在实现了 `LogStore` API 的分布式日志服务中。\n+ - WAL 的日志记录可以存储在本地磁盘上，也可以存储在实现了 `LogStore` API 的远程日志服务中，例如 Kafka（remote WAL）。\n - Memtable\n - 数据首先写入 `active memtable`，又称 `mutable memtable`。\n - 当 `mutable memtable` 已满时，它将变为只读的 `immutable memtable`。\n - SST\n - SST 的全名为有序字符串表（`Sorted String Table`）。\n - `immutable memtable` 刷到持久存储后形成一个 SST 文件。\n+ - SST 中的行按照主键和时间索引排序；详见 [SST 文件中的数据布局](#sst-文件中的数据布局)。\n - Compactor\n - `Compactor` 通过 compaction 操作将小的 SST 合并为大的 SST。\n- - 默认使用 [TWCS][3] 策略进行合并\n+ - 默认使用 [TWCS][3] 策略进行合并。Compaction 会按照时间窗口组织 SST 文件，并结合 TTL 清理过期数据。详见 [Compaction](/user-guide/deployments-administration/manage-data/compaction.md)。\n - Manifest\n - `Manifest` 存储引擎的元数据，例如 SST 的元数据。\n - Cache\n - 加速查询操作。\n \n [1]: https://en.wikipedia.org/wiki/Log-structured_merge-tree\n [2]: https://en.wikipedia.org/wiki/Write-ahead_logging\n [3]: https://cassandra.apache.org/doc/latest/cassandra/operating/compaction/twcs.html\n \n ## 数据模型\n \n 存储引擎提供的数据模型介于 `key-value` 模型和表模型之间\n \n ```txt\n tag-1, ..., tag-m, timestamp -> field-1, ..., field-n\n ```\n \n 每一行数据包含多个 tag 列，一个 timestamp 列和多个 field 列\n - `0 ~ m` 个 tag 列\n - tag 列是可空的\n - 在建表时通过 `PRIMARY KEY` 指定\n - 必须包含一个 timestamp 列\n - timestamp 列非空\n - 在建表时通过 `TIME INDEX` 指定\n - `0 ~ n` 个 field 列\n - field 列是可空的\n - 数据按照 tag 列和 timestamp 列有序存储\n \n ## Region\n \n 数据在存储引擎中以 `region` 的形式存储，`region` 是引擎中的一个逻辑隔离存储单元。`region` 中的行必须具有相同的 `schema`（模式），该 `schema` 定义了 `region` 中的 tag 列，timestamp 列和 field 列。数据库中表的数据存储在一到多个 `region` 中。\n+\n+## SST 文件中的数据布局\n+\n+当 memtable 被 flush 时，Mito 会把其中的行写入不可变的 [Apache Parquet](https://parquet.apache.org) SST 文件。关于 Parquet 文件格式本身以及 SST 文件如何建立索引，详见[数据持久化和索引](data-persistence-indexing.md)。\n+\n+在一个 SST 文件内，行按照 `(primary key, time index)` 排序。具有相同 primary key（tag 列）的行属于同一条时间序列，会连续存储并按时间戳排序。这种局部性使得扫描单条时间序列的成本更低，也有助于提升压缩效果。对于没有 primary key 的 append-only 表，行仅按 time index 排序。\n+\n+例如，考虑一个存储主机指标的表：\n+\n+```sql\n+CREATE TABLE host_metrics (\n+ host STRING,\n+ region STRING,\n+ ts TIMESTAMP TIME INDEX,\n+ cpu DOUBLE,\n+ memory DOUBLE,\n+ PRIMARY KEY (host, region)\n+);\n+```\n+\n+Mito 会按 primary key 对行分组，并按时间排序，因此 SST 中的数据在概念上类似于：\n+\n+| host | region | ts | cpu | memory |\n+| --- | --- | --- | --- | --- |\n+| host-a | us-east | 10:00 | 0.42 | 7.1 |\n+| host-a | us-east | 10:01 | 0.47 | 7.4 |\n+| host-a | us-west | 10:00 | 0.31 | 6.8 |\n+| host-b | us-east | 10:00 | 0.80 | 8.6 |\n+\n+除了表中的列，Mito 还会在每个 SST 文件中存储三个内部列，以便在从多个 memtable 和 SST 文件读取时正确地合并、去重并应用删除操作：\n+\n+- `__primary_key`：行的编码后 primary key（tags）。\n+- `__sequence`：行的 sequence number。\n+- `__op_type`：行的操作类型（put 或 delete）。\n+\n+每个 Parquet SST 都会被切分为 row group，row group 是 Parquet 可以独立读取或跳过的单位。每个 row group 都带有列统计信息，例如最小值、最大值和 null 数量。Mito 还会为每个 SST 记录文件级元数据，包括时间范围、行数、row group 数量、可用索引以及 primary key 范围。这些统计信息会驱动下面介绍的扫描裁剪。\n+\n+Mito 支持两种 SST 格式：`flat`（默认）和 `primary_key`。它们以不同方式编码 primary key，并针对不同的 primary key 基数进行优化。如何选择两种格式，详见 [SST format](/reference/sql/create.md#创建指定-sst-格式的表) 和[表设计指南](/user-guide/deployments-administration/performance-tuning/design-table.md#选择合适的-sst-格式)。\n+\n+ $\"SST$ \n+\n+## 扫描裁剪\n+\n+Mito 会组合多个从粗到细的裁剪步骤，避免读取不可能匹配查询的数据：\n+\n+1. **时间范围裁剪。** 如果文件和 memtable 的时间范围与查询时间范围不相交，就会在打开 reader 之前被跳过。对于时间序列查询，这通常是成本最低且最有效的步骤。\n+2. **Row group 统计信息。** 如果 row group 的 min-max 统计信息能够证明没有任何行匹配谓词，则会跳过整个 row group。\n+3. **索引。** 倒排索引、跳数索引和全文索引可以针对统计信息无法处理的谓词提供更精细的裁剪。详见[数据持久化和索引](data-persistence-indexing.md)。\n+\n+ $\"Scan$ \ndiff --git a/i18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/concepts/data-model.md b/i18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/concepts/data-model.md\nindex 035f9268a4d268efe843534c9eb0afdbc189d1fa..2e7eb8f8a977422d3c087bb3019c164eead54e6d 100644\n--- a/i18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/concepts/data-model.md\n+++ b/i18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/concepts/data-model.md\n@@ -1,44 +1,44 @@\n ---\n keywords: [数据模型, 表结构, 列类型, 设计考虑, 时序表, Tag, Timestamp, Field, Metrics, Logs, Traces]\n description: 介绍 GreptimeDB 的数据模型，包括表结构、列类型和设计考虑，适用于 metrics、logs 和 traces 数据。\n ---\n \n # 数据模型\n \n ## 模型\n \n GreptimeDB 使用时序表来组织、压缩和管理数据的过期。数据模型基于关系型数据库的表模型，同时针对 metrics、logs、traces 的特点做了适配。\n \n 所有数据按表组织，每个表中的列分为三种语义类型：`Tag`、`Timestamp` 和 `Field`。\n \n - 表名通常和指标名、日志源名或 metric 名称一致。\n - `Tag` 列标识时间序列的身份。相同 Tag 值的行属于同一条时间序列（有些 TSDB 也叫 label）。\n - `Timestamp` 是时序数据库的根基，表示数据的生成时间。每个表只能有一个 `Timestamp` 类型的列，也叫时间索引（`Time Index`）。\n - 其余列是 `Field` 列，存放实际的数据指标或日志内容，通常是数值或字符串，也可以是地理位置、时间戳等其他类型。\n \n-表按时间序列组织行，同一时间序列内按 `Timestamp` 排序。表还可以对相同 `Tag` + `Timestamp` 的行做去重，具体取决于业务需求。选择合适的表结构对查询和存储效率至关重要，详见[表设计指南](/user-guide/deployments-administration/performance-tuning/design-table.md)。\n+表按时间序列组织行，同一时间序列内按 `Timestamp` 排序。表还可以对相同 `Tag` + `Timestamp` 的行做去重，具体取决于业务需求。物理上，GreptimeDB 会把数据持久化为不可变的 Parquet SST 文件，行按照 `(primary key, timestamp)` 排序；当表没有 primary key（例如下面的 append-only 日志表）时，仅按照 timestamp 排序。要了解 SST 文件中的数据布局和裁剪方式，详见[存储引擎](/contributor-guide/datanode/storage-engine.md#sst-文件中的数据布局)文档。选择合适的表结构对查询和存储效率至关重要，详见[表设计指南](/user-guide/deployments-administration/performance-tuning/design-table.md)。\n \n ### Metrics\n \n 假设有一个 `system_metrics` 表，监控数据中心机器的资源使用：\n \n ```sql\n CREATE TABLE IF NOT EXISTS system_metrics (\n host STRING,\n idc STRING,\n cpu_util DOUBLE,\n memory_util DOUBLE,\n disk_util DOUBLE,\n ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,\n PRIMARY KEY(host, idc),\n TIME INDEX(ts)\n );\n ```\n \n 数据模型如下：\n \n ![time-series-table-model](/time-series-data-model.svg)\n \n 和常见的关系表模型很像，区别在于 `TIME INDEX` 约束——用来指定 `ts` 列为时间索引。\n \n - 表名 `system_metrics`。\ndiff --git a/i18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/deployments-administration/performance-tuning/design-table.md b/i18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/deployments-administration/performance-tuning/design-table.md\nindex d108a370e10ce78225ba753398299fdb3cf63360..5a44510574058ea496cd63205d982884ec0ca0c3 100644\n--- a/i18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/deployments-administration/performance-tuning/design-table.md\n+++ b/i18n/zh/docusaurus-plugin-content-docs/version-1.0/user-guide/deployments-administration/performance-tuning/design-table.md\n@@ -23,50 +23,53 @@ description: 详细介绍了 GreptimeDB 的数据模型使用指南，以及常\n 例如，`namespace`、`cluster`、`http_method` 通常是低基数的。\n - **高基数（High Cardinality）**：高基数列包含大量的唯一值。\n 例如，`trace_id`、`span_id`、`user_id`、`uri`、`ip`、`uuid`、`request_id`、表的自增 ID，时间戳通常是高基数的。\n \n \n ## 列类型\n \n 在 GreptimeDB 中，列被分为三种语义类型：`Tag`、`Field` 和 `Timestamp`。\n 时间戳通常表示数据采样的时间或日志/事件发生的时间。\n GreptimeDB 使用 `TIME INDEX` 约束来标识 `Timestamp` 列。\n 因此，`Timestamp` 列也被称为 `TIME INDEX` 列。\n 如果你有多个时间戳数据类型的列，你只能将其中一个定义为 `TIME INDEX`，其他的定义为 `Field` 列。\n \n 在 GreptimeDB 中，Tag 列是可选的。Tag 列的主要用途包括：\n \n 1. 定义存储时数据的排序方式。\n GreptimeDB 使用 `PRIMARY KEY` 约束来定义 tag 列和 tag 的排序顺序。\n 与传统数据库不同，GreptimeDB 的主键是用来定义时间序列的。\n GreptimeDB 中的表按照 `(primary key, timestamp)` 的顺序对行进行排序。\n 这提高了具有相同 tag 数据的局部性。\n 如果没有定义 tag 列，GreptimeDB 按时间戳对行进行排序。\n 2. 唯一标识一个时间序列。\n 当表不是 append-only 模式时，GreptimeDB 根据时间戳在同一时间序列（主键）下去除重复行。\n 3. 便于从使用 label 或 tag 的其他时序数据库迁移。\n \n+这种顺序就是磁盘上 Parquet SST 文件中的物理行布局。\n+要了解数据在 SST 文件中如何组织，以及这种排序、tag 基数和索引为什么会影响性能，详见[存储引擎](/contributor-guide/datanode/storage-engine.md#sst-文件中的数据布局)文档。\n+\n \n ## 主键\n \n ### 主键是可选的\n \n 错误的主键或索引可能会显著降低性能。\n 通常，你可以创建一个没有主键的仅追加表，因为对于许多场景来说，按时间戳排序数据已经有不错测性能了。\n 这也可以作为性能基准。\n \n ```sql\n CREATE TABLE http_logs (\n access_time TIMESTAMP TIME INDEX,\n application STRING,\n remote_addr STRING,\n http_status STRING,\n http_method STRING,\n http_refer STRING,\n user_agent STRING,\n request_id STRING,\n request STRING,\n ) with ('append_mode'='true');\n ```\n \n `http_logs` 表是存储 HTTP 服务器日志的示例。\n \ndiff --git a/versioned_docs/version-1.0/contributor-guide/datanode/data-persistence-indexing.md b/versioned_docs/version-1.0/contributor-guide/datanode/data-persistence-indexing.md\nindex 3d28c553b59a49e198127240f48707620b897f91..60c32dfdd8090ff6150a281997917422f52b4a62 100644\n--- a/versioned_docs/version-1.0/contributor-guide/datanode/data-persistence-indexing.md\n+++ b/versioned_docs/version-1.0/contributor-guide/datanode/data-persistence-indexing.md\n@@ -19,51 +19,51 @@ Second, data of the same column tends to be homogeneous which helps with compres\n \n $\"Parquet$ \n \n ## Data Persistence\n \n GreptimeDB provides a configuration item `storage.flush.global_write_buffer_size`, which is flush threshold of the total memory usage for all MemTables.\n \n When the size of data buffered in MemTables reaches that threshold, GreptimeDB will pick MemTables and flush them to SST files.\n \n ## Indexing Data in SST Files\n \n Apache Parquet file format provides inherent statistics in headers of column chunks and data pages, which are used for pruning and skipping.\n \n $\"Column$ \n \n For example, in the above Parquet file, if you want to filter rows where `name` = `Emily`, you can easily skip row group 0 because the max value for `name` field is `Charlie`. This statistical information reduces IO operations.\n \n ## Index Files\n \n For each SST file, GreptimeDB not only maintains an internal index but also generates a separate file to store the index structures specific to that SST file.\n \n The index files utilize the [Puffin][3] format, which offers significant flexibility, allowing for the storage of additional metadata and supporting a broader range of index structures.\n \n ![Puffin](/puffin.png)\n \n-Currently, the inverted index is the first supported index structure, and it is stored within the index file as a Blob.\n+GreptimeDB stores several index structures in the Puffin file as Blobs, including the inverted index, the skipping index (backed by a bloom filter), and the full-text index. The inverted index was the first one supported and is described in detail below.\n \n ## Inverted Index\n \n In version 0.7, GreptimeDB introduced the inverted index to accelerate queries.\n \n The inverted index is a common index structure used for full-text searches, mapping each word in the document to a list of documents containing that word. Greptime has adopted this technology, which originates from search engines, for use in the time series databases.\n \n Search engines and time series databases operate in separate domains, yet the principle behind the applied inverted index technology is similar. This similarity requires some conceptual adjustments:\n 1. Term: In GreptimeDB, it refers to the column value of the time series.\n 2. Document: In GreptimeDB, it refers to the data segment containing multiple time series.\n \n The inverted index enables GreptimeDB to skip data segments that do not meet query conditions, thus improving scanning efficiency.\n \n ![Inverted index searching](/inverted-index-searching.png)\n \n For instance, the query above uses the inverted index to identify data segments where `job` equals `apiserver`, `handler` matches the regex `.*users`, and `status` matches the regex `4...`. It then scans these data segments to produce the final results that meet all conditions, significantly reducing the number of IO operations.\n \n ### Inverted Index Format\n \n ![Inverted index format](/inverted-index-format.png)\n \n GreptimeDB builds inverted indexes by column, with each inverted index consisting of an FST and multiple Bitmaps.\n \n The FST (Finite State Transducer) enables GreptimeDB to store mappings from column values to Bitmap positions in a compact format and provides excellent search performance and supports complex search capabilities (such as regular expression matching). The Bitmaps maintain a list of data segment IDs, with each bit representing a data segment.\n \ndiff --git a/versioned_docs/version-1.0/contributor-guide/datanode/storage-engine.md b/versioned_docs/version-1.0/contributor-guide/datanode/storage-engine.md\nindex cc33ef94d99f41e818e2a773a05eaa9ee44d8a46..d6fedd7f392d61e4411e5d9e2644adb20763a708 100644\n--- a/versioned_docs/version-1.0/contributor-guide/datanode/storage-engine.md\n+++ b/versioned_docs/version-1.0/contributor-guide/datanode/storage-engine.md\n@@ -1,65 +1,116 @@\n ---\n keywords: [storage engine, LSMT, Mito engine, data model, architecture, compaction]\n description: Overview of the storage engine in GreptimeDB, its architecture, components, and data model.\n ---\n \n # Storage Engine\n \n ## Introduction\n \n The `storage engine` is responsible for storing the data of the database. Mito, based on [LSMT][1] (Log-structured Merge-tree), is the storage engine we use by default. We have made significant optimizations for handling time-series data scenarios, so mito engine is not suitable for general purposes.\n \n ## Architecture\n \n The picture below shows the architecture and process procedure of the storage engine.\n \n ![Architecture](/storage-engine-arch.png)\n \n The architecture is the same as a traditional LSMT engine:\n \n - [WAL][2]\n - Guarantees high durability for data that is not yet being flushed.\n - Based on the `Log Store` API, thus it doesn't care about the underlying storage\n media.\n- - Log records of the WAL can be stored in the local disk, or a distributed log service which\n- implements the `Log Store` API.\n+ - Log records of the WAL can be stored on the local disk, or in a remote log service such as\n+ Kafka (remote WAL) that implements the `Log Store` API.\n - Memtables:\n - Data is written into the `active memtable`, aka `mutable memtable` first.\n - When a `mutable memtable` is full, it will be changed to a `read-only memtable`, aka `immutable memtable`.\n - SST\n - The full name of SST, aka SSTable is `Sorted String Table`.\n - `Immutable memtable` is flushed to persistent storage and produces an SST file.\n+ - Rows in an SST are sorted by primary key and time index; see [Data Layout in SST Files](#data-layout-in-sst-files).\n - Compactor\n - Small `SST` is merged into large `SST` by the compactor via compaction.\n- - The default compaction strategy is [TWCS][3].\n+ - The default compaction strategy is [TWCS][3]. Compaction groups SST files into time windows and, together with TTL, removes expired data. See [Compaction](/user-guide/deployments-administration/manage-data/compaction.md).\n - Manifest\n - The manifest stores the metadata of the engine, such as the metadata of the `SST`.\n - Cache\n - Speed up queries.\n \n [1]: https://en.wikipedia.org/wiki/Log-structured_merge-tree\n [2]: https://en.wikipedia.org/wiki/Write-ahead_logging\n [3]: https://cassandra.apache.org/doc/latest/cassandra/operating/compaction/twcs.html\n \n ## Data Model\n \n The data model provided by the storage engine is between the `key-value` model and the tabular model.\n \n ```txt\n tag-1, ..., tag-m, timestamp -> field-1, ..., field-n\n ```\n \n Each row of data contains multiple tag columns, one timestamp column, and multiple field columns.\n - `0 ~ m` tag columns\n - Tag columns can be nullable.\n - Specified during table creation using `PRIMARY KEY`.\n - Must include one timestamp column\n - Timestamp column cannot be null.\n - Specified during table creation using `TIME INDEX`.\n - `0 ~ n` field columns\n - Field columns can be nullable.\n - Data is sorted by tag columns and timestamp column.\n \n ### Region\n \n Data in the storage engine is stored in `regions`, which are logical isolated storage units within the engine. Rows within a `region` must have the same `schema`, which defines the tag columns, timestamp column, and field columns within the `region`. The data of tables in the database is stored in one or multiple `regions`.\n+\n+## Data Layout in SST Files\n+\n+When a memtable is flushed, Mito writes its rows into immutable [Apache Parquet](https://parquet.apache.org) SST files. For the Parquet file format itself and how SST files are indexed, see [Data Persistence and Indexing](data-persistence-indexing.md).\n+\n+Within an SST file, rows are sorted by `(primary key, time index)`. Rows that share the same primary key (the tag columns) belong to the same time-series and are stored contiguously, ordered by timestamp. This locality is what makes scanning a single series cheap and improves compression. For append-only tables without a primary key, rows are sorted by the time index alone.\n+\n+For example, consider a table that stores host metrics:\n+\n+```sql\n+CREATE TABLE host_metrics (\n+ host STRING,\n+ region STRING,\n+ ts TIMESTAMP TIME INDEX,\n+ cpu DOUBLE,\n+ memory DOUBLE,\n+ PRIMARY KEY (host, region)\n+);\n+```\n+\n+Mito groups rows by primary key and orders them by time, so the data within an SST conceptually looks like:\n+\n+| host | region | ts | cpu | memory |\n+| --- | --- | --- | --- | --- |\n+| host-a | us-east | 10:00 | 0.42 | 7.1 |\n+| host-a | us-east | 10:01 | 0.47 | 7.4 |\n+| host-a | us-west | 10:00 | 0.31 | 6.8 |\n+| host-b | us-east | 10:00 | 0.80 | 8.6 |\n+\n+Besides the table columns, Mito stores three internal columns in each SST file so it can merge, deduplicate, and apply deletes correctly when reading from multiple memtables and SST files:\n+\n+- `__primary_key`: the encoded primary key (tags) of the row.\n+- `__sequence`: the sequence number of the row.\n+- `__op_type`: the operation type of the row (put or delete).\n+\n+Each Parquet SST is split into row groups, the unit that Parquet can read or skip independently. Every row group carries column statistics such as min value, max value, and null count. Mito also records file-level metadata for each SST, including the time range, row count, row-group count, available indexes, and the primary-key range. These statistics drive the scan pruning described below.\n+\n+Mito supports two SST formats, `flat` (the default) and `primary_key`, which encode the primary key differently and are tuned for different primary-key cardinalities. See [SST format](/reference/sql/create.md#create-a-table-with-sst-format) and the [table design guide](/user-guide/deployments-administration/performance-tuning/design-table.md#choosing-the-sst-format) for how to choose between them.\n+\n+ $\"SST$ \n+\n+## Scan Pruning\n+\n+Mito avoids reading data that cannot match a query by combining several pruning steps, from coarse to fine:\n+\n+1. **Time-range pruning.** Files and memtables whose time range does not intersect the query's time range are skipped before opening any reader. This is usually the cheapest and most effective step for time-series queries.\n+2. **Row-group statistics.** If a row group's min-max statistics prove that no row can match a predicate, the whole row group is skipped.\n+3. **Indexes.** Inverted, skipping, and full-text indexes provide more selective pruning for predicates that statistics cannot resolve. See [Data Persistence and Indexing](data-persistence-indexing.md).\n+\n+ $\"Scan$ \ndiff --git a/versioned_docs/version-1.0/user-guide/concepts/data-model.md b/versioned_docs/version-1.0/user-guide/concepts/data-model.md\nindex 455e8d62a6b0c1b46aa83fb466ae6b266718ad7b..30cd323436b87d0714c22209468027d738da66ae 100644\n--- a/versioned_docs/version-1.0/user-guide/concepts/data-model.md\n+++ b/versioned_docs/version-1.0/user-guide/concepts/data-model.md\n@@ -5,50 +5,51 @@ description: Describes the data model of GreptimeDB, focusing on time-series tab\n \n # Data Model\n \n ## Model\n \n GreptimeDB uses the [time-series](https://en.wikipedia.org/wiki/Time_series) table to guide the organization, compression, and expiration management of data.\n The data model is mainly based on the table model in relational databases while considering the characteristics of metrics, logs, and traces data.\n \n All data in GreptimeDB is organized into tables with names. Each data item in a table consists of three semantic types of columns: `Tag`, `Timestamp`, and `Field`.\n \n - Table names are often the same as the indicator names, log source names, or metric names.\n - `Tag` columns uniquely identify the time-series.\n Rows with the same `Tag` values belong to the same time-series.\n Some TSDBs may also call them labels.\n - `Timestamp` is the root of a metrics, logs, and traces database.\n It represents the date and time when the data was generated.\n A table can only have one column with the `Timestamp` semantic type, which is also called the `time index`.\n - The other columns are `Field` columns.\n Fields contain the data indicators or log contents that are collected.\n These fields are generally numerical values or string values,\n but may also be other types of data, such as geographic locations or timestamps.\n \n A table clusters rows of the same time-series and sorts rows of the same time-series by `Timestamp`.\n The table can also deduplicate rows with the same `Tag` and `Timestamp` values, depending on the requirements of the application.\n GreptimeDB stores and processes data by time-series.\n+Physically, GreptimeDB persists data into immutable Parquet SST files, sorting rows by `(primary key, timestamp)` — or by timestamp alone when a table has no primary key (such as the append-only logs table below). To learn how data is laid out and pruned inside SST files, see the [storage engine](/contributor-guide/datanode/storage-engine.md#data-layout-in-sst-files) documentation.\n Choosing the right schema is crucial for efficient data storage and retrieval; please refer to the [schema design guide](/user-guide/deployments-administration/performance-tuning/design-table.md) for more details.\n \n ### Metrics\n \n Suppose we have a table called `system_metrics` that monitors the resource usage of machines in data centers:\n \n ```sql\n CREATE TABLE IF NOT EXISTS system_metrics (\n host STRING,\n idc STRING,\n cpu_util DOUBLE,\n memory_util DOUBLE,\n disk_util DOUBLE,\n ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,\n PRIMARY KEY(host, idc),\n TIME INDEX(ts)\n );\n ```\n \n The data model for this table is as follows:\n \n ![time-series-table-model](/time-series-data-model.svg)\n \n This is very similar to the table model everyone is familiar with. The difference lies in the `TIME INDEX` constraint, which is used to specify the `ts` column as the time index column of this table.\n \ndiff --git a/versioned_docs/version-1.0/user-guide/deployments-administration/performance-tuning/design-table.md b/versioned_docs/version-1.0/user-guide/deployments-administration/performance-tuning/design-table.md\nindex dc4814a2f7141e07ee27d53c27d6a5a161abf75a..2d98804ab314bcc727d1ecccd738ceee88a6eab2 100644\n--- a/versioned_docs/version-1.0/user-guide/deployments-administration/performance-tuning/design-table.md\n+++ b/versioned_docs/version-1.0/user-guide/deployments-administration/performance-tuning/design-table.md\n@@ -25,50 +25,53 @@ Before proceeding, please review the GreptimeDB [Data Model Documentation](/user\n The total number of unique values usually no more than 10 thousand.\n For example, `namespace`, `cluster`, `http_method` are usually low cardinality.\n - **High Cardinality**: High cardinality columns contain a large number of unique values.\n For example, `trace_id`, `span_id`, `user_id`, `uri`, `ip`, `uuid`, `request_id`, table auto increment id, timestamps are usually high cardinality.\n \n ### Column Types\n \n In GreptimeDB, columns are categorized into three semantic types: `Tag`, `Field`, and `Timestamp`.\n The timestamp usually represents the time of data sampling or the occurrence time of logs/events.\n GreptimeDB uses the `TIME INDEX` constraint to identify the `Timestamp` column.\n So the `Timestamp` column is also called the `TIME INDEX` column.\n If you have multiple columns with timestamp data type, you can only define one as `TIME INDEX` and others as `Field` columns.\n \n In GreptimeDB, tag columns are optional. The main purposes of tag columns include:\n \n 1. Defining the ordering of data in storage.\n GreptimeDB reuses the `PRIMARY KEY` constraint to define tag columns and the ordering of tags.\n Unlike traditional databases, GreptimeDB defines time-series by the primary key.\n Tables in GreptimeDB sort rows in the order of `(primary key, timestamp)`.\n This improves the locality of data with the same tags.\n If there are no tag columns, GreptimeDB sorts rows by timestamp.\n 2. Identifying a unique time-series.\n When the table is not append-only, GreptimeDB can deduplicate rows by timestamp under the same time-series (primary key).\n 3. Smoothing migration from other TSDBs that use tags or labels.\n \n+This ordering is the physical layout of rows inside the Parquet SST files on disk.\n+To understand how data is organized in SST files and why this ordering, tag cardinality, and indexes affect performance, see the [storage engine](/contributor-guide/datanode/storage-engine.md#data-layout-in-sst-files) documentation.\n+\n \n ## Primary key\n \n ### Primary key is optional\n \n Bad primary key or index may significantly degrade performance.\n Generally you can create an append-only table without a primary key since ordering data by timestamp is sufficient for many workloads.\n It can also serve as a baseline.\n \n ```sql\n CREATE TABLE http_logs (\n access_time TIMESTAMP TIME INDEX,\n application STRING,\n remote_addr STRING,\n http_status STRING,\n http_method STRING,\n http_refer STRING,\n user_agent STRING,\n request_id STRING,\n request STRING,\n ) with ('append_mode'='true');\n ```\n \n The `http_logs` table is an example for storing HTTP server logs.\n \n","external_storage_diff",{"_2791":2792,"_2793":-5},"files_modified",12,"lines_added",175,"lines_removed","commit_message","additional_parent_commit_shas",[],"file_id","file_000000002a7871f79af3216567a9f274","ttl","partial_repo_snapshot","files",[],[2798],{"_2757":45,"_45":966},{"_91":505,"_41":83,"_95":505,"_2801":2802,"_2803":2804,"_2805":2806,"_131":-5,"_118":2807},[82],"input_items",[2824,2825,2826,2827,2828,2829,2830],"external_post_config",{"_2808":2809,"_443":376,"_2810":484,"_454":-5,"_2778":437,"_2811":-5,"_2812":2813,"_2814":2815,"_2816":-5,"_2817":-5,"_2818":2819,"_2820":15,"_2821":57,"_2822":52,"_2823":15},"user_model_slug","slug",1780982407.654401,"installation_id",99793971,"pr_number","review_trigger","comment_id",4656384948,"comment_type","issue","pr_write_guard_token","pending_pr_reaction_id","pending_comment_reaction_id",367439339,"comment_if_no_findings","comment_on_error","share_url","is_parallel_review",{"_91":964,"_95":505,"_959":2845},{"_491":492,"_493":494,"_2842":498,"_2843":128,"_501":-5,"_91":2844},{"_91":2831,"_493":2840,"_254":2841,"_2833":2837,"_2834":1791},{"_91":2831,"_493":2839,"_254":-5,"_2833":-5,"_2834":-5},{"_91":2831,"_493":2838,"_254":-5,"_2833":-5,"_2834":-5},{"_91":2831,"_493":2835,"_254":2836,"_2833":2837,"_2834":-5},{"_91":2831,"_493":2832,"_254":-5,"_2833":-5,"_2834":-5},"pull_request_comment","LGTM","side","line","**_{_{![P1 Badge](https://img.shields.io/badge/P1-orange?style=flat)}} Fix MDX style props to keep docs build working**\n\nIn this Docusaurus 3/MDX page, the `` tag is compiled as JSX and the `style` attribute is passed to React; a string value makes React SSR throw because `style` must be an object, so building this doc page will fail when it renders the new image. The same string-style pattern is used for the scan-pruning image below, so use a class or an object style such as `style={{ width: '80%', margin: '0 auto' }}` for both images.\n\nUseful? React with 👍 / 👎.","docs/contributor-guide/datanode/storage-engine.md","RIGHT","\n### 💡 Codex Review\n\nHere are some automated review suggestions for this pull request.\n\n**Reviewed commit:** `83ff57a1f4`\n \n\n

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