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markdown-pages/en/tidb/master/TOC.md

@@ -13,8 +13,8 @@
 - Get Started
   - [Quick Start with TiDB](/quick-start-with-tidb.md)
   - [Quick Start with HTAP](/quick-start-with-htap.md)
-  - [Learn TiDB SQL](/basic-sql-operations.md)
-  - [Learn HTAP](/explore-htap.md)
+  - [Explore SQL with TiDB](/basic-sql-operations.md)
+  - [Explore HTAP](/explore-htap.md)
   - [Import Example Database](/import-example-data.md)
 - Develop
   - [Overview](/develop/dev-guide-overview.md)
@@ -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)
   - Use PD Microservices
     - [PD Microservices Overview](/pd-microservices.md)
     - [Scale PD Microservice Nodes Using TiUP](/scale-microservices-using-tiup.md)
@@ -937,6 +938,7 @@
       - [Optimistic Transactions](/optimistic-transaction.md)
       - [Pessimistic Transactions](/pessimistic-transaction.md)
       - [Non-Transactional DML Statements](/non-transactional-dml.md)
+      - [Pipelined DML](/pipelined-dml.md)
     - [Views](/views.md)
     - [Partitioning](/partitioned-table.md)
     - [Temporary Tables](/temporary-tables.md)
@@ -1084,6 +1086,7 @@
   - v8.2
     - [8.2.0-DMR](/releases/release-8.2.0.md)
   - v8.1
+    - [8.1.2](/releases/release-8.1.2.md)
     - [8.1.1](/releases/release-8.1.1.md)
     - [8.1.0](/releases/release-8.1.0.md)
   - v8.0

markdown-pages/en/tidb/master/batch-processing.md

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+---
+title: Batch Data Processing
+summary: Introduces batch data processing features in TiDB, including Pipelined DML, non-transactional DML, the `IMPORT INTO` statement, and the deprecated batch-dml feature.
+---
+
+# Batch Data Processing
+
+Batch data processing is a common and essential operation in real-world scenarios. It enables efficient handling of large datasets for tasks such as data migration, bulk imports, archiving, and large-scale updates.
+
+To optimize performance for batch operations, TiDB introduces various features over its version evolution:
+
+- Data import
+    - `IMPORT INTO` statement (introduced in TiDB v7.2.0 and GA in v7.5.0)
+- Data inserts, updates, and deletions
+    - Pipelined DML (experimental, introduced in TiDB v8.0.0)
+    - Non-transactional DML (introduced in TiDB v6.1.0)
+    - Batch-dml (deprecated)
+
+This document outlines the key benefits, limitations, and use cases of these features to help you choose the most suitable solution for efficient batch data processing.
+
+## Data import
+
+The `IMPORT INTO` statement is designed for data import tasks. It allows you to quickly import data in formats such as CSV, SQL, or PARQUET into an empty TiDB table, without the need to deploy [TiDB Lightning](/tidb-lightning/tidb-lightning-overview.md) separately.
+
+### Key benefits
+
+- Extremely fast import speed
+- Easier to use compared to TiDB Lightning
+
+### Limitations
+
+- No transactional [ACID](/glossary.md#acid) guarantees
+- Subject to various usage restrictions
+
+### Use cases
+
+- Suitable for data import scenarios such as data migration or recovery. It is recommended to use `IMPORT INTO` instead of TiDB Lightning where applicable.
+
+For more information, see [`IMPORT INTO`](/sql-statements/sql-statement-import-into.md).
+
+## Data inserts, updates, and deletions
+
+### Pipelined DML
+
+Pipelined DML is an experimental feature introduced in TiDB v8.0.0. In v8.5.0, the feature is enhanced with significant performance improvements.
+
+#### Key benefits
+
+- 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
+- Achieves faster performance compared to standard DML
+- Can be enabled through system variables without SQL modifications
+
+#### Limitations
+
+- Only supports [autocommit](/transaction-overview.md#autocommit) `INSERT`, `REPLACE`, `UPDATE`, and `DELETE` statements.
+
+#### Use cases
+
+- Suitable for general batch data processing tasks, such as bulk data inserts, updates, and deletions.
+
+For more information, see [Pipelined DML](/pipelined-dml.md).
+
+### Non-transactional DML statements
+
+Non-transactional DML is introduced in TiDB v6.1.0. Initially, only the `DELETE` statement supports this feature. Starting from v6.5.0, `INSERT`, `REPLACE`, and `UPDATE` statements also supports this feature.
+
+#### Key benefits
+
+- Splits a single SQL statement into multiple smaller statements, bypassing memory limitations.
+- Achieves performance that is slightly faster or comparable to standard DML.
+
+#### Limitations
+
+- Only supports [autocommit](/transaction-overview.md#autocommit) statements
+- Requires modifications to SQL statements
+- Imposes strict requirements on SQL syntax; some statements might need rewriting
+- Lacks full transactional ACID guarantees; in case of failures, partial execution of a statement might occur
+
+#### Use cases
+
+- Suitable for scenarios involving bulk data inserts, updates, and deletions. Due to its limitations, it is recommended to consider non-transactional DML only when Pipelined DML is not applicable.
+
+For more details, refer to the [Non-transactional DML](/non-transactional-dml.md) documentation.
+
+### Deprecated batch-dml feature
+
+The batch-dml feature, available in TiDB versions prior to v4.0, is now deprecated and no longer recommended. This feature is controlled by the following system variables:
+
+- `tidb_batch_insert`
+- `tidb_batch_delete`
+- `tidb_batch_commit`
+- `tidb_enable_batch_dml`
+- `tidb_dml_batch_size`
+
+Due to the risk of data corruption or loss caused by inconsistent data and indexes, these variables have been deprecated and are planned for removal in future releases.
+
+It is **NOT RECOMMENDED** to use the deprecated batch-dml feature under any circumstances. Instead, consider other alternative features outlined in this document.

markdown-pages/en/tidb/master/pipelined-dml.md.md

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+---
+title: Pipelined DML
+summary: Introduces the use cases, methods, limitations, and FAQs of Pipelined DML. Pipelined DML enhances TiDB's batch processing capabilities, allowing transaction sizes to bypass TiDB's memory limits.
+---
+
+# Pipelined DML
+
+> **Warning:**
+>
+> Pipelined DML is an experimental feature. It is not recommended that you use it in the production environment. This feature might be changed or removed without prior notice. If you find a bug, you can report an [issue](https://github.com/pingcap/tidb/issues) on GitHub.
+
+This document introduces the use cases, methods, limitations, and common issues related to Pipelined DML.
+
+## Overview
+
+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:
+
+- 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.
+
+With pipelined DML enabled, you can achieve the following:
+
+- Perform large-scale data operations without being constrained by TiDB memory limits.
+- Maintain smoother workload and lower operation latency.
+- Keep transaction memory usage predictable, typically within 1 GiB.
+
+It is recommended to enable Pipelined DML in the following scenarios:
+
+- Processing data writes involving millions of rows or more
+- Encountering memory insufficient errors during DML operations
+- Experiencing noticeable workload fluctuations during large-scale data operations
+
+Note that although Pipelined DML significantly reduces memory usage during transaction processing, you still need to configure a [reasonable memory threshold](/system-variables.md#tidb_mem_quota_query) (at least 2 GiB recommended) to ensure other components (such as executors) function properly during large-scale data operations.
+
+## Limitations
+
+Currently, Pipelined DML has the following limitations:
+
+- Pipelined DML is currently incompatible with TiCDC, TiFlash, or BR. Avoid using Pipelined DML on tables associated with these components, as it might lead to issues such as blocking or OOM in these components.
+- Pipelined DML is not suitable for scenarios with write conflicts, because it might lead to significant performance degradation or operation failures that require rollback.
+- Make sure that the [metadata lock](/metadata-lock.md) is enabled during Pipelined DML operations.
+- When executing DML statements with Pipelined DML enabled, TiDB checks the following conditions. If any condition is not met, TiDB falls back to standard DML execution and generates a warning:
+    - Only [autocommit](/transaction-overview.md#autocommit) statements are supported.
+    - Only `INSERT`, `UPDATE`, `REPLACE`, and `DELETE` statements are supported.
+    - Target tables must not include [temporary tables](/temporary-tables.md) or [cached tables](/cached-tables.md).
+    - When [foreign key constraints](/foreign-key.md) are enabled (`foreign_key_checks = ON`), target tables must not include foreign key relationships.
+- When executing `INSERT IGNORE ... ON DUPLICATE KEY UPDATE` statements, conflicting updates might result in `Duplicate entry` errors.
+
+## Usage
+
+This section describes how to enable Pipelined DML and verify whether it takes effect.
+
+### Enable Pipelined DML
+
+You can enable Pipelined DML in one of the following methods:
+
+- To enable Pipelined DML for the current session, set the [`tidb_dml_type`](/system-variables.md#tidb_dml_type-new-in-v800) variable to `"bulk"`:
+
+    ```sql
+    SET tidb_dml_type = "bulk";
+    ```
+
+- To enable Pipelined DML for a specific statement, add the [`SET_VAR`](/optimizer-hints.md#set_varvar_namevar_value) hint in the statement.
+
+    - Data archiving example:
+
+        ```sql
+        INSERT /*+ SET_VAR(tidb_dml_type='bulk') */ INTO target_table SELECT * FROM source_table;
+        ```
+
+    - Bulk data update example:
+
+        ```sql
+        UPDATE /*+ SET_VAR(tidb_dml_type='bulk') */ products
+        SET price = price * 1.1
+        WHERE category = 'electronics';
+        ```
+
+    - Bulk deletion example:
+
+        ```sql
+        DELETE /*+ SET_VAR(tidb_dml_type='bulk') */ FROM logs WHERE log_time < '2023-01-01';
+        ```
+
+### Verify Pipelined DML
+
+After executing a DML statement, you can verify whether Pipelined DML is used for the statement execution by checking the [`tidb_last_txn_info`](/system-variables.md#tidb_last_txn_info-new-in-v409) variable:
+
+```sql
+SELECT @@tidb_last_txn_info;
+```
+
+If the `pipelined` field in the output is `true`, it indicates that Pipelined DML is successfully used.
+
+## Best practices
+
+- Increase the value of [`tidb_mem_quota_query`](/system-variables.md#tidb_mem_quota_query) slightly to ensure that memory usage for components such as executors does not exceed the limit. A value of at least 2 GiB is recommended. For environments with sufficient TiDB memory, you can increase this value further.
+- In scenarios where data is inserted into new tables, the performance of Pipelined DML might be affected by hotspots. To achieve optimal performance, it is recommended to address hotspots in advance. For more information, see [Troubleshoot Hotspot Issues](/troubleshoot-hot-spot-issues.md).
+
+## Related configurations
+
+- The [`tidb_dml_type`](/system-variables.md#tidb_dml_type-new-in-v800) system variable controls whether Pipelined DML is enabled at the session level.
+- When [`tidb_dml_type`](/system-variables.md#tidb_dml_type-new-in-v800) is set to `"bulk"`, the [`pessimistic-auto-commit`](/tidb-configuration-file.md#pessimistic-auto-commit) configuration item behaves as if it is set to `false`.
+- Transactions executed using Pipelined DML are not subject to the size limit specified by the TiDB configuration item [`txn-total-size-limit`](/tidb-configuration-file.md#txn-total-size-limit).
+- For large transactions executed using Pipelined DML, transaction duration might increase. In such cases, the maximum TTL for the transaction lock is the larger value of [`max-txn-ttl`](/tidb-configuration-file.md#max-txn-ttl) or 24 hours.
+- If the execution time of a transaction exceeds the value set by [`tidb_gc_max_wait_time`](/system-variables.md#tidb_gc_max_wait_time-new-in-v610), garbage collection (GC) might force the transaction to roll back, causing it to fail.
+
+## Monitor Pipelined DML
+
+You can monitor the execution of Pipelined DML using the following methods:
+
+- 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.
+
+## FAQs
+
+### Why wasn't my query executed using Pipelined DML?
+
+When TiDB rejects to execute a statement using Pipelined DML, it generates a warning message accordingly. You can execute `SHOW WARNINGS;` to check the warning and identify the cause.
+
+Common reasons:
+
+- The DML statement is not autocommited.
+- The statement involves unsupported table types, such as [temporary tables](/temporary-tables.md) or [cached tables](/cached-tables.md).
+- The operation involves foreign keys, and foreign key checks are enabled.
+
+### Does Pipelined DML affect the isolation level of transactions?
+
+No. Pipelined DML only changes the data-writing mechanism during transactions and does not affect isolation guarantees of TiDB transactions.
+
+### Why do I still encounter out-of-memory (OOM) errors after enabling Pipelined DML?
+
+Even with Pipelined DML enabled, you might still encounter query termination caused by memory limit issues:
+
+```
+The query has been canceled due to exceeding the memory limit allowed for a single SQL query. Please try to narrow the query scope or increase the tidb_mem_quota_query limit, and then try again.
+```
+
+This error occurs because Pipelined DML only controls the memory usage by data during transaction execution. However, the total memory consumed during statement execution also includes memory used by other components, such as executors. If the total memory required exceeds TiDB memory limit, out-of-memory (OOM) errors might still occur.
+
+In most cases, you can increase the system variable [`tidb_mem_quota_query`](/system-variables.md#tidb_mem_quota_query) to a higher value to resolve this issue. A value of at least 2 GiB is recommended. For SQL statements with complex operators or involving large datasets, you might need to increase this value further.
+
+## Learn More
+
+- [Batch Data Processing](/batch-processing.md)
+- [TiDB Memory Control](/configure-memory-usage.md)