Runtime Filter

Runtime Filter 是 TiDB v7.3 引入的新功能,旨在提升 MPP 场景下 Hash Join 的性能。它通过动态生成 Filter 来提前过滤 Hash Join 的数据,从而减少运行时的数据扫描量以及 Hash Join 的计算量,最终提升查询性能。

名词解释

  • Hash Join:一种实现 Join 关系代数的方式。它通过在 Join 的一侧构建 Hash Table 并在另一侧不断匹配 Hash Table 来得到 Join 的结果。
  • Build Side:Hash Join 中用于构建 Hash Table 的一侧,称为 Build Side。本文默认以 Join 的右表作为 Build Side。
  • Probe Side:Hash Join 中用于不断匹配 Hash Table 的一侧,称为 Probe Side。本文默认以 Join 的左表作为 Probe Side。
  • Filter:也称谓词,在本文中指过滤条件。

Runtime Filter 的原理

Hash Join 通过将右表的数据构建为 Hash Table,并将左表的数据不断匹配 Hash Table 来完成 Join。如果在匹配过程中,发现一部分 Join Key 值无法命中 Hash Table,则说明这部分数据不存在于右表,也不会出现在最终的 Join 结果中。因此,如果能够在扫描时提前过滤掉这部分 Join Key 的数据,将减少扫描时间和网络开销,从而大幅提升 Join 效率。

Runtime Filter 是在查询规划阶段生成的一种动态取值谓词。该谓词与 TiDB Selection 中的其他谓词具有相同作用,都应用于 Table Scan 操作上,用于筛选不满足谓词条件的行为。唯一的区别在于,Runtime Filter 中的参数取值来自于 Hash Join 构建过程中产生的结果。

示例

假设当前存在 store_sales 表与 date_dim 表的 Join 查询,它的 Join 方式为 Hash Join。store_sales 是一张事实表,主要存储门店销售数据,行数为 100 万。date_dim 是一张时间维度表,主要存储日期信息。当前想要查询 2001 年的销售数据,则 date_dim 表参与 Join 的数据量为 365 行。

SELECT * FROM store_sales, date_dim WHERE ss_date_sk = d_date_sk AND d_year = 2001;

Hash Join 通常情况下的执行方式为:

+-------------------+ | PhysicalHashJoin | +------->| |<------+ | +-------------------+ | | | | | 100w | | 365 | | | | +-------+-------+ +--------+-------+ | TableFullScan | | TableFullScan | | store_sales | | date_dim | +---------------+ +----------------+

(上图为示意图,省略了 exchange 等节点)

Runtime Filter 的执行方式如下:

  1. 扫描 date_dim 的数据。
  2. PhysicalHashJoin 根据 Build Side 数据计算出一个过滤条件,比如 date_dim in (2001/01/01~2001/12/31)
  3. 将该过滤条件发送给等待扫描 store_sales 的 TableFullScan。
  4. store_sales 应用该过滤条件,并将过滤后的数据传递给 PhysicalHashJoin,从而减少 Probe Side 的扫表数据量以及匹配 Hash Table 的计算量。
2. Build RF values +-------->+-------------------+ | |PhysicalHashJoin |<-----+ | +----+ | | 4. After RF | | +-------------------+ | 1. Scan T2 5000 | |3. Send RF | 365 | | filter data | | | | +-----+----v------+ +-------+--------+ | TableFullScan | | TableFullScan | | store_sales | | date_dim | +-----------------+ +----------------+
  • (上图中的 RF 是 Runtime Filter 的缩写) *

对比以上两个图可以看出,store_sales 的扫描量从 100 万减少到了 5000。通过减少 Table Full Scan 扫描的数据量,Runtime Filter 可以减少匹配 Hash Table 的次数,避免不必要的 I/O 和网络传输,从而显著提升了 Join 操作的效率。

使用 Runtime Filter

要使用 Runtime Filter,只需创建带 TiFlash 副本的表,并将 tidb_runtime_filter_mode 设置为 LOCAL

本小节以 TPC-DS 的数据集为例,使用 catalog_sales 表和 date_dim 表进行 Join 操作,说明如何使用 Runtime Filter 提升查询效率。

第 1 步:创建表的 TiFlash 副本

catalog_sales 表和 date_dim 表分别增加一个 TiFlash 副本。

ALTER TABLE catalog_sales SET tiflash REPLICA 1; ALTER TABLE date_dim SET tiflash REPLICA 1;

等待一段时间,并检查两个表的 TiFlash 副本已准备就绪,即副本的 AVAILABLE 字段和 PROGRESS 字段均为 1

SELECT * FROM INFORMATION_SCHEMA.TIFLASH_REPLICA WHERE TABLE_NAME='catalog_sales'; +--------------+---------------+----------+---------------+-----------------+-----------+----------+ | TABLE_SCHEMA | TABLE_NAME | TABLE_ID | REPLICA_COUNT | LOCATION_LABELS | AVAILABLE | PROGRESS | +--------------+---------------+----------+---------------+-----------------+-----------+----------+ | tpcds50 | catalog_sales | 1055 | 1 | | 1 | 1 | +--------------+---------------+----------+---------------+-----------------+-----------+----------+ mysql> SELECT * FROM INFORMATION_SCHEMA.TIFLASH_REPLICA WHERE TABLE_NAME='date_dim'; +--------------+------------+----------+---------------+-----------------+-----------+----------+ | TABLE_SCHEMA | TABLE_NAME | TABLE_ID | REPLICA_COUNT | LOCATION_LABELS | AVAILABLE | PROGRESS | +--------------+------------+----------+---------------+-----------------+-----------+----------+ | tpcds50 | date_dim | 1015 | 1 | | 1 | 1 | +--------------+------------+----------+---------------+-----------------+-----------+----------+

第 2 步:开启 Runtime Filter

将系统变量 tidb_runtime_filter_mode 的值设置为 LOCAL,即开启 Runtime Filter。

SET tidb_runtime_filter_mode="LOCAL";

查看是否更改成功:

SHOW VARIABLES LIKE "tidb_runtime_filter_mode"; +--------------------------+-------+ | Variable_name | Value | +--------------------------+-------+ | tidb_runtime_filter_mode | LOCAL | +--------------------------+-------+

系统变量的值显示为 LOCAL,则表示已成功开启 Runtime Filter。

第 3 步:执行查询

在进行查询之前,先查看一下查询计划。使用 EXPLAIN 语句来检查 Runtime Filter 是否已正确生效。

EXPLAIN SELECT cs_ship_date_sk FROM catalog_sales, date_dim WHERE d_date = '2002-2-01' AND cs_ship_date_sk = d_date_sk;

当 Runtime Filter 启用时,可以看到 HashJoin 节点和 TableScan 节点上分别挂载了对应的 Runtime Filter,表示 Runtime Filter 规划成功。

TableFullScan: runtime filter:0[IN] -> tpcds50.catalog_sales.cs_ship_date_sk HashJoin: runtime filter:0[IN] <- tpcds50.date_dim.d_date_sk |

完整的查询规划如下:

+----------------------------------------+-------------+--------------+---------------------+-----------------------------------------------------------------------------------------------------------------------------------------------+ | id | estRows | task | access object | operator info | +----------------------------------------+-------------+--------------+---------------------+-----------------------------------------------------------------------------------------------------------------------------------------------+ | TableReader_53 | 37343.19 | root | | MppVersion: 1, data:ExchangeSender_52 | | └─ExchangeSender_52 | 37343.19 | mpp[tiflash] | | ExchangeType: PassThrough | | └─Projection_51 | 37343.19 | mpp[tiflash] | | tpcds50.catalog_sales.cs_ship_date_sk | | └─HashJoin_48 | 37343.19 | mpp[tiflash] | | inner join, equal:[eq(tpcds50.date_dim.d_date_sk, tpcds50.catalog_sales.cs_ship_date_sk)], runtime filter:0[IN] <- tpcds50.date_dim.d_date_sk | | ├─ExchangeReceiver_29(Build) | 1.00 | mpp[tiflash] | | | | │ └─ExchangeSender_28 | 1.00 | mpp[tiflash] | | ExchangeType: Broadcast, Compression: FAST | | │ └─TableFullScan_26 | 1.00 | mpp[tiflash] | table:date_dim | pushed down filter:eq(tpcds50.date_dim.d_date, 2002-02-01 00:00:00.000000), keep order:false | | └─Selection_31(Probe) | 71638034.00 | mpp[tiflash] | | not(isnull(tpcds50.catalog_sales.cs_ship_date_sk)) | | └─TableFullScan_30 | 71997669.00 | mpp[tiflash] | table:catalog_sales | pushed down filter:empty, keep order:false, runtime filter:0[IN] -> tpcds50.catalog_sales.cs_ship_date_sk | +----------------------------------------+-------------+--------------+---------------------+-----------------------------------------------------------------------------------------------------------------------------------------------+ 9 rows in set (0.01 sec)

此时执行 SQL 查询,即可应用 Runtime Filter。

SELECT cs_ship_date_sk FROM catalog_sales, date_dim WHERE d_date = '2002-2-01' AND cs_ship_date_sk = d_date_sk;

第 4 步:性能对比

以 TPC-DS 的 50 GB 数据量为例,开启 Runtime Filter 后,查询时间从 0.38 秒减少到 0.17 秒,效率提升 50%。通过 ANALYZE 语句可以查看 Runtime Filter 生效后各个算子的执行时间。

以下为未开启 Runtime Filter 时查询的执行信息:

EXPLAIN ANALYZE SELECT cs_ship_date_sk FROM catalog_sales, date_dim WHERE d_date = '2002-2-01' AND cs_ship_date_sk = d_date_sk; +----------------------------------------+-------------+----------+--------------+---------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------+---------+------+ | id | estRows | actRows | task | access object | execution info | operator info | memory | disk | +----------------------------------------+-------------+----------+--------------+---------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------+---------+------+ | TableReader_53 | 37343.19 | 59574 | root | | time:379.7ms, loops:83, RU:0.000000, cop_task: {num: 48, max: 0s, min: 0s, avg: 0s, p95: 0s, copr_cache_hit_ratio: 0.00} | MppVersion: 1, data:ExchangeSender_52 | 12.0 KB | N/A | | └─ExchangeSender_52 | 37343.19 | 59574 | mpp[tiflash] | | tiflash_task:{proc max:377ms, min:375.3ms, avg: 376.1ms, p80:377ms, p95:377ms, iters:1160, tasks:2, threads:16} | ExchangeType: PassThrough | N/A | N/A | | └─Projection_51 | 37343.19 | 59574 | mpp[tiflash] | | tiflash_task:{proc max:377ms, min:375.3ms, avg: 376.1ms, p80:377ms, p95:377ms, iters:1160, tasks:2, threads:16} | tpcds50.catalog_sales.cs_ship_date_sk | N/A | N/A | | └─HashJoin_48 | 37343.19 | 59574 | mpp[tiflash] | | tiflash_task:{proc max:377ms, min:375.3ms, avg: 376.1ms, p80:377ms, p95:377ms, iters:1160, tasks:2, threads:16} | inner join, equal:[eq(tpcds50.date_dim.d_date_sk, tpcds50.catalog_sales.cs_ship_date_sk)] | N/A | N/A | | ├─ExchangeReceiver_29(Build) | 1.00 | 2 | mpp[tiflash] | | tiflash_task:{proc max:291.3ms, min:290ms, avg: 290.6ms, p80:291.3ms, p95:291.3ms, iters:2, tasks:2, threads:16} | | N/A | N/A | | │ └─ExchangeSender_28 | 1.00 | 1 | mpp[tiflash] | | tiflash_task:{proc max:290.9ms, min:0s, avg: 145.4ms, p80:290.9ms, p95:290.9ms, iters:1, tasks:2, threads:1} | ExchangeType: Broadcast, Compression: FAST | N/A | N/A | | │ └─TableFullScan_26 | 1.00 | 1 | mpp[tiflash] | table:date_dim | tiflash_task:{proc max:3.88ms, min:0s, avg: 1.94ms, p80:3.88ms, p95:3.88ms, iters:1, tasks:2, threads:1}, tiflash_scan:{dtfile:{total_scanned_packs:2, total_skipped_packs:12, total_scanned_rows:16384, total_skipped_rows:97625, total_rs_index_load_time: 0ms, total_read_time: 0ms}, total_create_snapshot_time: 0ms, total_local_region_num: 1, total_remote_region_num: 0} | pushed down filter:eq(tpcds50.date_dim.d_date, 2002-02-01 00:00:00.000000), keep order:false | N/A | N/A | | └─Selection_31(Probe) | 71638034.00 | 71638034 | mpp[tiflash] | | tiflash_task:{proc max:47ms, min:34.3ms, avg: 40.6ms, p80:47ms, p95:47ms, iters:1160, tasks:2, threads:16} | not(isnull(tpcds50.catalog_sales.cs_ship_date_sk)) | N/A | N/A | | └─TableFullScan_30 | 71997669.00 | 71997669 | mpp[tiflash] | table:catalog_sales | tiflash_task:{proc max:34ms, min:17.3ms, avg: 25.6ms, p80:34ms, p95:34ms, iters:1160, tasks:2, threads:16}, tiflash_scan:{dtfile:{total_scanned_packs:8893, total_skipped_packs:4007, total_scanned_rows:72056474, total_skipped_rows:32476901, total_rs_index_load_time: 8ms, total_read_time: 579ms}, total_create_snapshot_time: 0ms, total_local_region_num: 194, total_remote_region_num: 0} | pushed down filter:empty, keep order:false | N/A | N/A | +----------------------------------------+-------------+----------+--------------+---------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------+---------+------+ 9 rows in set (0.38 sec)

以下为开启 Runtime Filter 后的查询 Summary:

EXPLAIN ANALYZE SELECT cs_ship_date_sk FROM catalog_sales, date_dim -> WHERE d_date = '2002-2-01' AND -> cs_ship_date_sk = d_date_sk; +----------------------------------------+-------------+---------+--------------+---------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------+---------+------+ | id | estRows | actRows | task | access object | execution info | operator info | memory | disk | +----------------------------------------+-------------+---------+--------------+---------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------+---------+------+ | TableReader_53 | 37343.19 | 59574 | root | | time:162.1ms, loops:82, RU:0.000000, cop_task: {num: 47, max: 0s, min: 0s, avg: 0s, p95: 0s, copr_cache_hit_ratio: 0.00} | MppVersion: 1, data:ExchangeSender_52 | 12.7 KB | N/A | | └─ExchangeSender_52 | 37343.19 | 59574 | mpp[tiflash] | | tiflash_task:{proc max:160.8ms, min:154.3ms, avg: 157.6ms, p80:160.8ms, p95:160.8ms, iters:86, tasks:2, threads:16} | ExchangeType: PassThrough | N/A | N/A | | └─Projection_51 | 37343.19 | 59574 | mpp[tiflash] | | tiflash_task:{proc max:160.8ms, min:154.3ms, avg: 157.6ms, p80:160.8ms, p95:160.8ms, iters:86, tasks:2, threads:16} | tpcds50.catalog_sales.cs_ship_date_sk | N/A | N/A | | └─HashJoin_48 | 37343.19 | 59574 | mpp[tiflash] | | tiflash_task:{proc max:160.8ms, min:154.3ms, avg: 157.6ms, p80:160.8ms, p95:160.8ms, iters:86, tasks:2, threads:16} | inner join, equal:[eq(tpcds50.date_dim.d_date_sk, tpcds50.catalog_sales.cs_ship_date_sk)], runtime filter:0[IN] <- tpcds50.date_dim.d_date_sk | N/A | N/A | | ├─ExchangeReceiver_29(Build) | 1.00 | 2 | mpp[tiflash] | | tiflash_task:{proc max:132.3ms, min:130.8ms, avg: 131.6ms, p80:132.3ms, p95:132.3ms, iters:2, tasks:2, threads:16} | | N/A | N/A | | │ └─ExchangeSender_28 | 1.00 | 1 | mpp[tiflash] | | tiflash_task:{proc max:131ms, min:0s, avg: 65.5ms, p80:131ms, p95:131ms, iters:1, tasks:2, threads:1} | ExchangeType: Broadcast, Compression: FAST | N/A | N/A | | │ └─TableFullScan_26 | 1.00 | 1 | mpp[tiflash] | table:date_dim | tiflash_task:{proc max:3.01ms, min:0s, avg: 1.51ms, p80:3.01ms, p95:3.01ms, iters:1, tasks:2, threads:1}, tiflash_scan:{dtfile:{total_scanned_packs:2, total_skipped_packs:12, total_scanned_rows:16384, total_skipped_rows:97625, total_rs_index_load_time: 0ms, total_read_time: 0ms}, total_create_snapshot_time: 0ms, total_local_region_num: 1, total_remote_region_num: 0} | pushed down filter:eq(tpcds50.date_dim.d_date, 2002-02-01 00:00:00.000000), keep order:false | N/A | N/A | | └─Selection_31(Probe) | 71638034.00 | 5308995 | mpp[tiflash] | | tiflash_task:{proc max:39.8ms, min:24.3ms, avg: 32.1ms, p80:39.8ms, p95:39.8ms, iters:86, tasks:2, threads:16} | not(isnull(tpcds50.catalog_sales.cs_ship_date_sk)) | N/A | N/A | | └─TableFullScan_30 | 71997669.00 | 5335549 | mpp[tiflash] | table:catalog_sales | tiflash_task:{proc max:36.8ms, min:23.3ms, avg: 30.1ms, p80:36.8ms, p95:36.8ms, iters:86, tasks:2, threads:16}, tiflash_scan:{dtfile:{total_scanned_packs:660, total_skipped_packs:12451, total_scanned_rows:5335549, total_skipped_rows:100905778, total_rs_index_load_time: 2ms, total_read_time: 47ms}, total_create_snapshot_time: 0ms, total_local_region_num: 194, total_remote_region_num: 0} | pushed down filter:empty, keep order:false, runtime filter:0[IN] -> tpcds50.catalog_sales.cs_ship_date_sk | N/A | N/A | +----------------------------------------+-------------+---------+--------------+---------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------+---------+------+ 9 rows in set (0.17 sec)

对比两个查询的执行信息,可发现以下改进:

  • IO 减少:对比 TableFullScan 算子的 total_scanned_rows 可知,开启 Runtime Filter 后 TableFullScan 的扫描量减少了 2/3 。
  • Hash Join 性能提升:HashJoin 算子的执行耗时从 376.1ms 减少至 157.6ms。

最佳实践

Runtime Filter 适用于大表和小表进行 Join 的情况,比如事实表和维度表的关联查询。当维度表的命中的数据量较少时,意味着 Filter 的取值较少,事实表能更多地过滤掉不满足条件的数据。与默认情况下扫描整个事实表相比,这将显著提高查询性能。

例如,在 TPC-DS 中,泛 Sales 表和 date_dim 表的 Join 就是一个典型例子。

配置 Runtime Filter

在使用 Runtime Filter 时,你可以配置 Runtime Filter 的模式和谓词的类型。

Runtime Filter Mode

Runtime Filter Mode 指的是 Runtime Filter 的模式,即 生成 Filter 算子接收 Filter 算子之间的关系。共有三种模式:OFFLOCALGLOBAL。在 v7.3.0 中仅支持 OFFLOCAL 模式,通过系统变量 tidb_runtime_filter_mode 控制。

  • OFF:代表关闭 Runtime Filter。关闭后,查询行为和过去完全一致。
  • LOCAL:开启 LOCAL 模式的 Runtime Filter。LOCAL 模式指的是生成 Filter 的算子接收 Filter 的算子在同一个 MPP Task 中。简单来说,Runtime Filter 可应用于 HashJoin 算子和 TableScan 算子在同一个 Task 中的情况。目前 Runtime Filter 仅支持 LOCAL 模式,要开启该模式,设置为 LOCAL 即可。
  • GLOBAL:目前不支持 GLOBAL 模式,不可设置为该模式。

Runtime Filter Type

Runtime Filter Type 指的是 Runtime Filter 谓词的类型,即生成的 Filter 算子使用的谓词类型。目前只支持一种类型:IN,即生成的谓词类似于 k1 in (xxx)。通过系统变量 tidb_runtime_filter_type 控制。

  • IN:默认为 IN 类型。即生成的 Runtime Filter 使用 IN 类型的谓词。

限制

  • Runtime Filter 是 MPP 架构下的优化,仅可应用于下推到 TiFlash 的查询。
  • Join 类型:Left outer、Full outer、Anti join(当左表为 Probe Side 时)均不支持生成 Runtime Filter。由于 Runtime Filter 会提前过滤参与 Join 的数据,这些类型的 Join 不会丢弃未匹配上的数据,所以无法使用该优化。
  • Equal Join expression:当等值 Join 表达式中的 Probe 列为复杂表达式,或者其类型为 JSON、Blob、Array 等复合类型时,也不会生成 Runtime Filter。主要原因是这类 Column 很少作为 Equal Join 的关联列,并且即使生成了 Filter,过滤率通常很低。

对于以上限制,如果你需要确认是否正确生成了 Runtime Filter,可以通过 EXPLAIN 语句 来验证。

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