doc: batch processing overview and pipelined dml #19818
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| @@ -397,6 +397,7 @@ | |||
| - [Use Load Base Split](/configure-load-base-split.md) | |||
| - [Use Store Limit](/configure-store-limit.md) | |||
| - [DDL Execution Principles and Best Practices](/ddl-introduction.md) | |||
| - [Batch Data Processing](/batch-processing.md) | |||
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Batch processing is a more commonly used term, I suppose?
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| - Data import | ||
| - `IMPORT INTO` statement (introduced in TiDB v7.2.0 and GA in v7.5.0) | ||
| - Data inserts, updates, and deletions |
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| #### Key benefits | ||
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| - Streams data to the storage layer during transaction execution instead of caching it entirely in memory, allowing transaction size no longer limited by TiDB memory and supporting ultra-large-scale data processing |
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| - Streams data to the storage layer during transaction execution instead of caching it entirely in memory, allowing transaction size no longer limited by TiDB memory and supporting ultra-large-scale data processing | |
| - Streams data to the storage layer during transaction execution instead of buffering it entirely in memory, allowing transaction size no longer limited by TiDB memory and supporting ultra-large-scale data processing |
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| ## Overview | ||
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| Pipelined DML is an experimental feature introduced in TiDB v8.0.0 to improve the performance of large-scale data write operations. When this feature is enabled, TiDB streams data directly to the storage layer during DML operations, instead of caching it entirely in memory. This pipeline-like approach simultaneously reads data (input) and writes it to the storage layer (output), effectively resolving common challenges in large-scale DML operations as follows: |
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| Pipelined DML is an experimental feature introduced in TiDB v8.0.0 to improve the performance of large-scale data write operations. When this feature is enabled, TiDB streams data directly to the storage layer during DML operations, instead of caching it entirely in memory. This pipeline-like approach simultaneously reads data (input) and writes it to the storage layer (output), effectively resolving common challenges in large-scale DML operations as follows: | |
| Pipelined DML is an experimental feature introduced in TiDB v8.0.0 to improve the performance of large-scale data write operations. When this feature is enabled, TiDB streams data directly to the storage layer during DML operations, instead of buffering it entirely in memory. This pipeline-like approach simultaneously reads data (input) and writes it to the storage layer (output), effectively resolving common challenges in large-scale DML operations as follows: |
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| - Memory limits: traditional DML operations might encounter out-of-memory (OOM) errors when handling large datasets. | ||
| - Performance bottlenecks: large transactions are often inefficient and is prone to causing workload fluctuations. | ||
| - Operational limits: TiDB memory limits make it difficult to execute ultra-large data processing tasks. |
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How about removing this point as it's a duplicate of the 1st point? Also for the Chinese doc.
| - Check the [`tidb_last_txn_info`](/system-variables.md#tidb_last_txn_info-new-in-v409) system variable to get information about the last transaction executed in the current session, including whether Pipelined DML was used. | ||
| - Look for lines containing `"[pipelined dml]"` in TiDB logs to understand the execution process and progress of Pipelined DML, including the current stage and the amount of data written. | ||
| - View the `affected rows` field in the [`expensive query`](/identify-expensive-queries.md#expensive-query-log-example) logs to track the progress of long-running statements. | ||
| - Query the [`INFORMATION_SCHEMA.PROCESSLIST`](/information-schema/information-schema-processlist.md) table to view transaction execution progress. Pipelined DML is typically used for large transactions, so you can use this table monitor their execution progress. |
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| - Query the [`INFORMATION_SCHEMA.PROCESSLIST`](/information-schema/information-schema-processlist.md) table to view transaction execution progress. Pipelined DML is typically used for large transactions, so you can use this table monitor their execution progress. | |
| - Query the [`INFORMATION_SCHEMA.PROCESSLIST`](/information-schema/information-schema-processlist.md) table to view transaction execution progress. Pipelined DML is typically used for large transactions, so you can use this table to monitor their execution progress. |
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