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移除书签TiFlash 性能调优
对于希望节省机器资源，并且完全没有隔离要求的场景，可以使用 TiKV 和 TiFlash 联合部署。建议为 TiKV 与 TiFlash 分别留够资源，同时避免共享磁盘。
TiDB 相关参数调优
本部分介绍如何通过调整 TiDB 相关参数来提升 TiFlash 性能，具体包括如下几个方面：
MPP 执行计划可以充分利用分布式计算资源，从而显著提高批量数据查询的效率。当查询没有生成 MPP 执行计划的时候，你可以强制开启 MPP：
tidb_enforce_mpp 变量用于控制是否忽略优化器代价估算，强制使用 TiFlash 的 MPP 模式执行查询。要开启 MPP 模式查询，执行如下命令：
在以下示例中，tidb_enforce_mpp 开启前，TiDB 需要从 TiKV 读取数据，并在 TiDB 侧执行 Join 和 Aggregation。tidb_enforce_mpp 开启后，Join 和 Aggregation 被下推到了 TiFlash。需要注意的是，有时候优化器生成的执行计划并不稳定，可能生成 MPP，也可能不生成，这时候可以开启 tidb_enforce_mpp，强制优化器生成 MPP 计划。
MPP 模式开启前：
mysql> explain analyze select o_orderpriority, count(*) as order_count from orders where o_orderdate >= '1995-01-01' and o_orderdate < date_add('1995-01-01', interval '3' month) and exists (select * from lineitem where l_orderkey = o_orderkey and l_commitdate < l_receiptdate) group by o_orderpriority;+--------------------------------------+--------------+-----------+-----------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------------+------+| id | estRows | actRows | task | access object | execution info | operator info | memory | disk |+--------------------------------------+--------------+-----------+-----------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------------+------+| Projection_9 | 1.00 | 5 | root | | time:22.8s, loops:5, Concurrency:OFF | tpch_100.orders.o_orderpriority, Column#27 | 1016 Bytes | N/A || └─HashAgg_10 | 1.00 | 5 | root | | time:22.8s, loops:5, partial_worker:{wall_time:22.817403422s, concurrency:5, task_num:5027, tot_wait:1m52.560509138s, tot_exec:1.523754659s, tot_time:1m54.086196522s, max:22.817363394s, p95:22.817363394s}, final_worker:{wall_time:22.817416046s, concurrency:5, task_num:20, tot_wait:1m54.086784741s, tot_exec:155.94µs, tot_time:1m54.086948982s, max:22.817396284s, p95:22.817396284s} | group by:tpch_100.orders.o_orderpriority, funcs:count(1)->Column#27, funcs:firstrow(tpch_100.orders.o_orderpriority)->tpch_100.orders.o_orderpriority | 511.7 KB | N/A || └─IndexHashJoin_18 | 4429262.13 | 5145138 | root | | time:22.8s, loops:5028, inner:{total:1m52.6s, concurrency:5, task:227, construct:5.17s, fetch:1m40s, build:1.22s, join:7.49s} | semi join, inner:IndexLookUp_15, outer key:tpch_100.orders.o_orderkey, inner key:tpch_100.lineitem.l_orderkey, equal cond:eq(tpch_100.orders.o_orderkey, tpch_100.lineitem.l_orderkey) | 46.8 MB | N/A || ├─TableReader_37(Build) | 5536577.67 | 5610951 | root | | time:4.89s, loops:5467, cop_task: {num: 2127, max: 408.7ms, min: 277.5µs, avg: 81.6ms, p95: 249.7ms, max_proc_keys: 226272, p95_proc_keys: 220128, tot_proc: 2m50.2s, tot_wait: 40ms, rpc_num: 2127, rpc_time: 2m53.6s, copr_cache_hit_ratio: 0.02, distsql_concurrency: 15} | data:Selection_36 | 3.42 MB | N/A || │ └─Selection_36 | 5536577.67 | 5610951 | cop[tikv] | | tikv_task:{proc max:402ms, min:0s, avg: 79.7ms, p80:151ms, p95:245ms, iters:155122, tasks:2127}, scan_detail: {total_process_keys: 149478336, total_process_keys_size: 22705157593, total_keys: 149480413, get_snapshot_time: 187.9ms, rocksdb: {key_skipped_count: 149478336, block: {cache_hit_count: 393690}}} | ge(tpch_100.orders.o_orderdate, 1995-01-01 00:00:00.000000), lt(tpch_100.orders.o_orderdate, 1995-04-01 00:00:00.000000) | N/A | N/A || │ └─TableFullScan_35 | 150000000.00 | 150000000 | cop[tikv] | table:orders | tikv_task:{proc max:382ms, min:0s, avg: 74.6ms, p80:141ms, p95:229ms, iters:155122, tasks:2127} | keep order:false | N/A | N/A || └─IndexLookUp_15(Probe) | 22018496.89 | 14185840 | root | | time:1m33.4s, loops:14204, index_task: {total_time: 1m10.8s, fetch_handle: 1m10.7s, build: 3.9ms, wait: 13.3ms}, table_task: {total_time: 1m44.4s, num: 1989, concurrency: 5} | | 17.9 KB | N/A || ├─IndexRangeScan_12(Build) | 27523121.11 | 22441356 | cop[tikv] | table:lineitem, index:PRIMARY(L_ORDERKEY, L_LINENUMBER) | time:1m8.8s, loops:23635, cop_task: {num: 12537, max: 179.3ms, min: 331.4µs, avg: 22.7ms, p95: 66.9ms, max_proc_keys: 13755, p95_proc_keys: 5088, tot_proc: 3m44s, tot_wait: 129ms, rpc_num: 12537, rpc_time: 4m44s, copr_cache_hit_ratio: 0.06, distsql_concurrency: 15}, tikv_task:{proc max:170ms, min:0s, avg: 18.8ms, p80:29ms, p95:62ms, iters:68823, tasks:12537}, scan_detail: {total_process_keys: 21985403, total_process_keys_size: 1165226359, total_keys: 27492546, get_snapshot_time: 563.1ms, rocksdb: {key_skipped_count: 21985403, block: {cache_hit_count: 44004354}}} | range: decided by [eq(tpch_100.lineitem.l_orderkey, tpch_100.orders.o_orderkey)], keep order:false | N/A | N/A || └─Selection_14(Probe) | 22018496.89 | 14185840 | cop[tikv] | | time:1m34.8s, loops:16882, cop_task: {num: 12057, max: 240.4ms, min: 328.5µs, avg: 20.4ms, p95: 73.1ms, max_proc_keys: 15005, p95_proc_keys: 6118, tot_proc: 3m39.8s, tot_wait: 300ms, rpc_num: 12057, rpc_time: 4m5.7s, copr_cache_hit_ratio: 0.28, distsql_concurrency: 15}, tikv_task:{proc max:230ms, min:0s, avg: 27.5ms, p80:45ms, p95:82ms, iters:74165, tasks:12057}, scan_detail: {total_process_keys: 19916937, total_process_keys_size: 3957799619, total_keys: 24053143, get_snapshot_time: 1.07s, rocksdb: {key_skipped_count: 19254567, block: {cache_hit_count: 37816908}}} | lt(tpch_100.lineitem.l_commitdate, tpch_100.lineitem.l_receiptdate) | N/A | N/A || └─TableRowIDScan_13 | 27523121.11 | 22441356 | cop[tikv] | table:lineitem | tikv_task:{proc max:230ms, min:0s, avg: 27.2ms, p80:45ms, p95:81ms, iters:74165, tasks:12057} | keep order:false | N/A | N/A |+--------------------------------------+--------------+-----------+-----------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------------+------+10 rows in set (22.82 sec)
开启 MPP 模式：
mysql> set @@tidb_enforce_mpp = ON;Query OK, 0 rows affected (0.00 sec)
MPP 模式开启后：
mysql> explain analyze select o_orderpriority, count(*) as order_count from orders where o_orderdate >= '1995-01-01' and o_orderdate < date_add('1995-01-01', interval '3' month) and exists (select * from lineitem where l_orderkey = o_orderkey and l_commitdate < l_receiptdate) group by o_orderpriority;+--------------------------------------------------+--------------+-----------+--------------+----------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------+------+| id | estRows | actRows | task | access object | execution info | operator info | memory | disk |+--------------------------------------------------+--------------+-----------+--------------+----------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------+------+| TableReader_59 | 1.00 | 5 | root | | time:5.97s, loops:2, cop_task: {num: 8, max: 0s, min: 0s, avg: 0s, p95: 0s, copr_cache_hit_ratio: 0.00} | data:ExchangeSender_58 | N/A | N/A || └─ExchangeSender_58 | 1.00 | 5 | mpp[tiflash] | | tiflash_task:{proc max:5.97s, min:5.97s, avg: 5.97s, p80:5.97s, p95:5.97s, iters:5, tasks:3, threads:60} | ExchangeType: PassThrough | N/A | N/A || └─Projection_10 | 1.00 | 5 | mpp[tiflash] | | tiflash_task:{proc max:5.97s, min:5.96s, avg: 5.97s, p80:5.97s, p95:5.97s, iters:5, tasks:3, threads:60} | tpch_100.orders.o_orderpriority, Column#27 | N/A | N/A || └─Projection_54 | 1.00 | 5 | mpp[tiflash] | | tiflash_task:{proc max:5.97s, min:5.96s, avg: 5.97s, p80:5.97s, p95:5.97s, iters:5, tasks:3, threads:60} | Column#27, tpch_100.orders.o_orderpriority | N/A | N/A || └─HashAgg_55 | 1.00 | 5 | mpp[tiflash] | | tiflash_task:{proc max:5.97s, min:5.96s, avg: 5.97s, p80:5.97s, p95:5.97s, iters:5, tasks:3, threads:60} | group by:tpch_100.orders.o_orderpriority, funcs:sum(Column#32)->Column#27, funcs:firstrow(tpch_100.orders.o_orderpriority)->tpch_100.orders.o_orderpriority, stream_count: 20 | N/A | N/A || └─ExchangeReceiver_57 | 1.00 | 15 | mpp[tiflash] | | tiflash_task:{proc max:5.97s, min:5.96s, avg: 5.97s, p80:5.97s, p95:5.97s, iters:5, tasks:3, threads:60} | stream_count: 20 | N/A | N/A || └─ExchangeSender_56 | 1.00 | 15 | mpp[tiflash] | | tiflash_task:{proc max:5.96s, min:0s, avg: 1.99s, p80:5.96s, p95:5.96s, iters:768, tasks:3, threads:60} | ExchangeType: HashPartition, Hash Cols: [name: tpch_100.orders.o_orderpriority, collate: utf8mb4_bin], stream_count: 20 | N/A | N/A || └─HashAgg_52 | 1.00 | 15 | mpp[tiflash] | | tiflash_task:{proc max:5.96s, min:0s, avg: 1.99s, p80:5.96s, p95:5.96s, iters:768, tasks:3, threads:60} | group by:tpch_100.orders.o_orderpriority, funcs:count(1)->Column#32 | N/A | N/A || └─HashJoin_41 | 4429262.13 | 5145138 | mpp[tiflash] | | tiflash_task:{proc max:5.95s, min:0s, avg: 1.98s, p80:5.95s, p95:5.95s, iters:118, tasks:3, threads:60} | semi join, equal:[eq(tpch_100.orders.o_orderkey, tpch_100.lineitem.l_orderkey)], stream_count: 20 | N/A | N/A || ├─ExchangeReceiver_26(Build) | 480030321.60 | 379356474 | mpp[tiflash] | | tiflash_task:{proc max:3.26s, min:0s, avg: 1.09s, p80:3.26s, p95:3.26s, iters:42469, tasks:3, threads:60} | stream_count: 20 | N/A | N/A || │ └─ExchangeSender_25 | 480030321.60 | 379356474 | mpp[tiflash] | | tiflash_task:{proc max:3.37s, min:0s, avg: 1.12s, p80:3.37s, p95:3.37s, iters:9292, tasks:3, threads:60} | ExchangeType: HashPartition, Hash Cols: [name: tpch_100.lineitem.l_orderkey, collate: binary], stream_count: 20 | N/A | N/A || │ └─Projection_60 | 480030321.60 | 379356474 | mpp[tiflash] | | tiflash_task:{proc max:819.1ms, min:0s, avg: 273ms, p80:819.1ms, p95:819.1ms, iters:9292, tasks:3, threads:60} | tpch_100.lineitem.l_orderkey | N/A | N/A || │ └─Selection_24 | 480030321.60 | 379356474 | mpp[tiflash] | | tiflash_task:{proc max:817.1ms, min:0s, avg: 272.4ms, p80:817.1ms, p95:817.1ms, iters:9292, tasks:3, threads:60} | lt(tpch_100.lineitem.l_commitdate, tpch_100.lineitem.l_receiptdate) | N/A | N/A || │ └─TableFullScan_23 | 600037902.00 | 600037902 | mpp[tiflash] | table:lineitem | tiflash_task:{proc max:328.1ms, min:0s, avg: 109.4ms, p80:328.1ms, p95:328.1ms, iters:9292, tasks:3, threads:60}, tiflash_scan:{dtfile:{total_scanned_packs:73475, total_skipped_packs:13452, total_scanned_rows:600230532, total_skipped_rows:109887612, total_rs_index_load_time: 35ms, total_read_time: 34065ms}, total_create_snapshot_time: 0ms} | keep order:false | N/A | N/A || └─ExchangeReceiver_22(Probe) | 5536577.67 | 5610951 | mpp[tiflash] | | tiflash_task:{proc max:2.5s, min:0s, avg: 833.7ms, p80:2.5s, p95:2.5s, iters:669, tasks:3, threads:60} | | N/A | N/A || └─ExchangeSender_21 | 5536577.67 | 5610951 | mpp[tiflash] | | tiflash_task:{proc max:5.93s, min:0s, avg: 1.98s, p80:5.93s, p95:5.93s, iters:2336, tasks:3, threads:60} | ExchangeType: HashPartition, Hash Cols: [name: tpch_100.orders.o_orderkey, collate: binary] | N/A | N/A || └─Selection_20 | 5536577.67 | 5610951 | mpp[tiflash] | | tiflash_task:{proc max:325.5ms, min:0s, avg: 108.5ms, p80:325.5ms, p95:325.5ms, iters:2336, tasks:3, threads:60} | ge(tpch_100.orders.o_orderdate, 1995-01-01 00:00:00.000000), lt(tpch_100.orders.o_orderdate, 1995-04-01 00:00:00.000000) | N/A | N/A || └─TableFullScan_19 | 150000000.00 | 150000000 | mpp[tiflash] | table:orders | tiflash_task:{proc max:238.5ms, min:0s, avg: 79.5ms, p80:238.5ms, p95:238.5ms, iters:2336, tasks:3, threads:60}, tiflash_scan:{dtfile:{total_scanned_packs:18541, total_skipped_packs:186, total_scanned_rows:150000611, total_skipped_rows:1513328, total_rs_index_load_time: 75ms, total_read_time: 11454ms}, total_create_snapshot_time: 0ms} | keep order:false | N/A | N/A |+--------------------------------------------------+--------------+-----------+--------------+----------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------+------+18 rows in set (6.00 sec)
聚合下推 Join 或 Union
将聚合操作下推到 Join 或 Union 之前执行，有可能能显著减少 Join 或 Union 需要处理的数据量，从而提升性能。
tidb_opt_agg_push_down 变量用来设置优化器是否执行聚合函数下推到 Join 之前的优化操作。当查询中聚合操作执行很慢时，可以尝试设置该变量为 ON。
set @@tidb_opt_agg_push_down = ON;
在以下示例中，tidb_opt_agg_push_down 开启前，HashAgg_58 在 HashJoin_41 之后执行。tidb_opt_agg_push_down 开启后，新生成的 HashAgg_21 和 HashAgg_32 在 HashJoin_76 之前执行，显著减少了 Join 需要处理的数据量。
tidb_opt_agg_push_down 开启前:
mysql> explain analyze select count(*) from t1 join t2 where t1.a = t2.b group by t1.a;+------------------------------------------+--------------+-----------+--------------+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------+--------+------+| id | estRows | actRows | task | access object | execution info | operator info | memory | disk |+------------------------------------------+--------------+-----------+--------------+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------+--------+------+| TableReader_66 | 100450000.00 | 20 | root | | time:2.13s, loops:2, cop_task: {num: 21, max: 0s, min: 0s, avg: 0s, p95: 0s, copr_cache_hit_ratio: 0.00} | data:ExchangeSender_65 | N/A | N/A || └─ExchangeSender_65 | 100450000.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:2.13s, min:2.08s, avg: 2.11s, p80:2.13s, p95:2.13s, iters:768, tasks:3, threads:60} | ExchangeType: PassThrough | N/A | N/A || └─Projection_60 | 100450000.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:2.13s, min:2.08s, avg: 2.11s, p80:2.13s, p95:2.13s, iters:768, tasks:3, threads:60} | Column#43 | N/A | N/A || └─HashAgg_58 | 100450000.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:2.13s, min:2.08s, avg: 2.11s, p80:2.13s, p95:2.13s, iters:768, tasks:3, threads:60} | group by:test.t1.a, funcs:count(1)->Column#43 | N/A | N/A || ├─ExchangeReceiver_22(Build) | 100450000.00 | 99980000 | mpp[tiflash] | | tiflash_task:{proc max:171ms, min:127ms, avg: 154.5ms, p80:171ms, p95:171ms, iters:10440, tasks:3, threads:60} | stream_count: 20 | N/A | N/A || │ └─ExchangeSender_21 | 100450000.00 | 99980000 | mpp[tiflash] | | tiflash_task:{proc max:498.7ms, min:0s, avg: 166.2ms, p80:498.7ms, p95:498.7ms, iters:1653, tasks:3, threads:60} | ExchangeType: HashPartition, Hash Cols: [name: test.t1.a, collate: binary], stream_count: 20 | N/A | N/A || │ └─Selection_20 | 100450000.00 | 99980000 | mpp[tiflash] | | tiflash_task:{proc max:83.7ms, min:0s, avg: 27.9ms, p80:83.7ms, p95:83.7ms, iters:1653, tasks:3, threads:60} | not(isnull(test.t1.a)) | N/A | N/A || │ └─TableFullScan_19 | 100450000.00 | 99980000 | mpp[tiflash] | table:t1 | tiflash_task:{proc max:41.7ms, min:0s, avg: 13.9ms, p80:41.7ms, p95:41.7ms, iters:1653, tasks:3, threads:60}, tiflash_scan:{dtfile:{total_scanned_packs:12336, total_skipped_packs:5759, total_scanned_rows:100083566, total_skipped_rows:46786721, total_rs_index_load_time: 5ms, total_read_time: 1105ms}, total_create_snapshot_time: 0ms} | keep order:false | N/A | N/A || └─ExchangeReceiver_26(Probe) | 600000000.00 | 600000000 | mpp[tiflash] | | tiflash_task:{proc max:373ms, min:71ms, avg: 253.2ms, p80:373ms, p95:373ms, iters:28135, tasks:3, threads:60} | | N/A | N/A || └─ExchangeSender_25 | 600000000.00 | 600000000 | mpp[tiflash] | | tiflash_task:{proc max:2.07s, min:0s, avg: 689.6ms, p80:2.07s, p95:2.07s, iters:9388, tasks:3, threads:60} | ExchangeType: HashPartition, Hash Cols: [name: test.t2.b, collate: binary] | N/A | N/A || └─TableFullScan_23 | 600000000.00 | 600000000 | mpp[tiflash] | table:t2 | tiflash_task:{proc max:63.8ms, min:0s, avg: 21.3ms, p80:63.8ms, p95:63.8ms, iters:9388, tasks:3, threads:60}, tiflash_scan:{dtfile:{total_scanned_packs:73834, total_skipped_packs:439, total_scanned_rows:600007458, total_skipped_rows:3553131, total_rs_index_load_time: 12ms, total_read_time: 270ms}, total_create_snapshot_time: 0ms} | keep order:false | N/A | N/A |+------------------------------------------+--------------+-----------+--------------+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------+--------+------+13 rows in set (2.15 sec)
mysql> set @@tidb_opt_agg_push_down = ON;Query OK, 0 rows affected (0.00 sec)
开启 tidb_opt_agg_push_down 后：
mysql> explain analyze select count(*) from t1 join t2 where t1.a = t2.b group by t1.a;+------------------------------------------------------+--------------+-----------+--------------+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------+--------+------+| id | estRows | actRows | task | access object | execution info | operator info | memory | disk |+------------------------------------------------------+--------------+-----------+--------------+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------+--------+------+| TableReader_85 | 20.00 | 20 | root | | time:432.4ms, loops:2, cop_task: {num: 19, max: 0s, min: 0s, avg: 0s, p95: 0s, copr_cache_hit_ratio: 0.00} | data:ExchangeSender_84 | N/A | N/A || └─ExchangeSender_84 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:431.1ms, min:429.3ms, avg: 430.4ms, p80:431.1ms, p95:431.1ms, iters:16, tasks:3, threads:60} | ExchangeType: PassThrough | N/A | N/A || └─Projection_83 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:430.1ms, min:429.3ms, avg: 429.7ms, p80:430.1ms, p95:430.1ms, iters:16, tasks:3, threads:60} | Column#43 | N/A | N/A || └─HashAgg_82 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:430.1ms, min:429.3ms, avg: 429.7ms, p80:430.1ms, p95:430.1ms, iters:16, tasks:3, threads:60} | group by:test.t1.a, funcs:count(Column#44)->Column#43, stream_count: 20 | N/A | N/A || └─ExchangeReceiver_78 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:430.1ms, min:429.3ms, avg: 429.7ms, p80:430.1ms, p95:430.1ms, iters:16, tasks:3, threads:60} | stream_count: 20 | N/A | N/A || └─ExchangeSender_77 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:427ms, min:0s, avg: 142.3ms, p80:427ms, p95:427ms, iters:60, tasks:3, threads:60} | ExchangeType: HashPartition, Hash Cols: [name: test.t1.a, collate: binary], stream_count: 20 | N/A | N/A || └─HashJoin_76 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:426ms, min:0s, avg: 142ms, p80:426ms, p95:426ms, iters:60, tasks:3, threads:60} | inner join, equal:[eq(test.t1.a, test.t2.b)] | N/A | N/A || ├─ExchangeReceiver_36(Build) | 20.00 | 60 | mpp[tiflash] | | tiflash_task:{proc max:374ms, min:0s, avg: 124.7ms, p80:374ms, p95:374ms, iters:46, tasks:3, threads:60} | | N/A | N/A || │ └─ExchangeSender_35 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:373.7ms, min:0s, avg: 124.6ms, p80:373.7ms, p95:373.7ms, iters:16, tasks:3, threads:60} | ExchangeType: Broadcast | N/A | N/A || │ └─Projection_31 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:373.7ms, min:0s, avg: 124.6ms, p80:373.7ms, p95:373.7ms, iters:16, tasks:3, threads:60} | Column#44, test.t2.b | N/A | N/A || │ └─HashAgg_32 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:373.7ms, min:0s, avg: 124.6ms, p80:373.7ms, p95:373.7ms, iters:16, tasks:3, threads:60} | group by:test.t2.b, funcs:sum(Column#45)->Column#44, funcs:firstrow(test.t2.b)->test.t2.b, stream_count: 20 | N/A | N/A || │ └─ExchangeReceiver_34 | 20.00 | 60 | mpp[tiflash] | | tiflash_task:{proc max:373.7ms, min:0s, avg: 124.6ms, p80:373.7ms, p95:373.7ms, iters:16, tasks:3, threads:60} | stream_count: 20 | N/A | N/A || │ └─ExchangeSender_33 | 20.00 | 60 | mpp[tiflash] | | tiflash_task:{proc max:368.3ms, min:0s, avg: 122.8ms, p80:368.3ms, p95:368.3ms, iters:3, tasks:3, threads:60} | ExchangeType: HashPartition, Hash Cols: [name: test.t2.b, collate: binary], stream_count: 20 | N/A | N/A || │ └─HashAgg_21 | 20.00 | 60 | mpp[tiflash] | | tiflash_task:{proc max:367.3ms, min:0s, avg: 122.4ms, p80:367.3ms, p95:367.3ms, iters:3, tasks:3, threads:60} | group by:test.t2.b, funcs:count(1)->Column#45 | N/A | N/A || │ └─Selection_30 | 600000000.00 | 600000000 | mpp[tiflash] | | tiflash_task:{proc max:77.2ms, min:0s, avg: 25.7ms, p80:77.2ms, p95:77.2ms, iters:9389, tasks:3, threads:60} | not(isnull(test.t2.b)) | N/A | N/A || │ └─TableFullScan_29 | 600000000.00 | 600000000 | mpp[tiflash] | table:t2 | tiflash_task:{proc max:37.2ms, min:0s, avg: 12.4ms, p80:37.2ms, p95:37.2ms, iters:9389, tasks:3, threads:60}, tiflash_scan:{dtfile:{total_scanned_packs:73834, total_skipped_packs:412, total_scanned_rows:600002896, total_skipped_rows:3342145, total_rs_index_load_time: 0ms, total_read_time: 45ms}, total_create_snapshot_time: 0ms} | keep order:false | N/A | N/A || └─Selection_19(Probe) | 100450000.00 | 99980000 | mpp[tiflash] | | tiflash_task:{proc max:30ms, min:0s, avg: 10ms, p80:30ms, p95:30ms, iters:1645, tasks:3, threads:60} | not(isnull(test.t1.a)) | N/A | N/A || └─TableFullScan_18 | 100450000.00 | 99980000 | mpp[tiflash] | table:t1 | tiflash_task:{proc max:22ms, min:0s, avg: 7.34ms, p80:22ms, p95:22ms, iters:1645, tasks:3, threads:60}, tiflash_scan:{dtfile:{total_scanned_packs:12326, total_skipped_packs:4762, total_scanned_rows:100045535, total_skipped_rows:38651216, total_rs_index_load_time: 4ms, total_read_time: 355ms}, total_create_snapshot_time: 0ms} | keep order:false | N/A | N/A |+------------------------------------------------------+--------------+-----------+--------------+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------+--------+------+18 rows in set (0.46 sec)
TiFlash 暂时还不支持部分可接受 Distinct 列的聚合函数，比如 Sum 。默认情况下，整个聚合函数运算都会在 TiDB 端执行。通过开启 Distinct 优化，部分操作可以下推到 TiFlash，从而提升查询性能：
tidb_opt_distinct_agg_push_down 变量用来设置优化器是否执行带有 Distinct 的聚合函数（比如 select sum(distinct a) from t）下推到 Coprocessor 的优化操作。当查询中带有 Distinct 的聚合操作执行很慢时，可以尝试设置该变量为 ON。
set @@tidb_opt_distinct_agg_push_down = ON;
在以下示例中，tidb_opt_distinct_agg_push_down 开启前，TiDB 需要从 TiFlash 读取所有数据，并在 TiDB 侧执行 distinct。tidb_opt_distinct_agg_push_down 开启后，distinct a 被下推到了 TiFlash，在 HashAgg_6 里新增里一个 group by 列 test.t.a。这边查询结果里面的两个 warnings 是警告聚合函数不能完全下推。
tidb_opt_distinct_agg_push_down 开启前：
开启 tidb_opt_distinct_agg_push_down：
mysql> set @@tidb_opt_distinct_agg_push_down = ON;Query OK, 0 rows affected (0.00 sec)
tidb_opt_distinct_agg_push_down 开启后：
mysql> explain analyze select count(distinct a) from test.t;+-----------------------------+--------------+-----------+-------------------+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------+-----------+---------+| id | estRows | actRows | task | access object | execution info | operator info | memory | disk |+-----------------------------+--------------+-----------+-------------------+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------+-----------+---------+| HashAgg_10 | 1.00 | 1 | root | | time:233.8ms, loops:2 | funcs:sum(distinct Column#23)->Column#22 | 2.42 KB | 0 Bytes || └─Projection_12 | 1.00 | 3 | root | | time:233.7ms, loops:2, Concurrency:OFF | cast(test.c.a, decimal(10,0) BINARY)->Column#23 | 380 Bytes | N/A || └─TableReader_11 | 1.00 | 3 | root | | time:233.7ms, loops:2, cop_task: {num: 6, max: 0s, min: 0s, avg: 0s, p95: 0s, copr_cache_hit_ratio: 0.00, distsql_concurrency: 15} | data:HashAgg_6 | 100 Bytes | N/A || └─HashAgg_6 | 1.00 | 3 | batchCop[tiflash] | | tiflash_task:{proc max:225.8ms, min:210.7ms, avg: 216.9ms, p80:225.8ms, p95:225.8ms, iters:3, tasks:3, threads:60} | group by:test.t.a, | N/A | N/A || └─TableFullScan_9 | 600000000.00 | 600000000 | batchCop[tiflash] | table:t | tiflash_task:{proc max:50.3ms, min:33.7ms, avg: 44.6ms, p80:50.3ms, p95:50.3ms, iters:9387, tasks:3, threads:60}, tiflash_scan:{dtfile:{total_scanned_packs:73833, total_skipped_packs:475, total_scanned_rows:600000000, total_skipped_rows:3852098, total_rs_index_load_time: 0ms, total_read_time: 84ms}, total_create_snapshot_time: 0ms} | keep order:false | N/A | N/A |+-----------------------------+--------------+-----------+-------------------+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------+-----------+---------+5 rows in set, 2 warnings (0.24 sec)
使用 ALTER TABLE...COMPACT 整理数据
ALTER TABLE … COMPACT 可以触发 TiFlash 节点对某个表或者某个分区进行数据整理。数据整理时，表中的物理数据会被重写，如清理已删除的数据、合并多版本数据等，从而可以获得更高的访问性能，并减少磁盘空间占用。
ALTER TABLE employees COMPACT TIFLASH REPLICA;
ALTER TABLE employees COMPACT PARTITION pNorth, pEast TIFLASH REPLICA;
对于有小表的 Join 算子，Broadcast Hash Join 可以避免大表的网络传输，从而提升计算性能。
tidb_broadcast_join_threshold_size，单位为 bytes。如果表大小（字节数）小于该值，则选择 Broadcast Hash Join 算法。否则选择 Shuffled Hash Join 算法。
set @@tidb_broadcast_join_threshold_size = 2000000;
，单位为行数。如果 join 的对象为子查询，优化器无法估计子查询结果集大小，在这种情况下通过结果集行数判断。如果子查询的行数估计值小于该变量，则选择 Broadcast Hash Join 算法。否则选择 Shuffled Hash Join 算法。
set @@tidb_broadcast_join_threshold_count = 100000;
在以下示例中，tidb_broadcast_join_threshold_size 设置前，ExchangeSender_29 的 ExchangeType 是 HashPartition。tidb_broadcast_join_threshold_size 设置后，ExchangeSender_29 的 ExchangeType 改变为 Broadcast。
mysql> explain analyze select max(l_shipdate), max(l_commitdate), max(l_receiptdate) from supplier,lineitem where s_suppkey = l_suppkey;+------------------------------------------+--------------+-----------+--------------+----------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------+---------+------+| id | estRows | actRows | task | access object | execution info | operator info | memory | disk |+------------------------------------------+--------------+-----------+--------------+----------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------+---------+------+| HashAgg_45 | 1.00 | 1 | root | | time:3.8s, loops:2, partial_worker:{wall_time:3.798284809s, concurrency:5, task_num:1, tot_wait:18.99079929s, tot_exec:8.193µs, tot_time:18.990819019s, max:3.798181723s, p95:3.798181723s}, final_worker:{wall_time:0s, concurrency:5, task_num:1, tot_wait:18.991291379s, tot_exec:197.45µs, tot_time:18.991494363s, max:3.798334972s, p95:3.798334972s} | funcs:max(Column#28)->Column#25, funcs:max(Column#29)->Column#26, funcs:max(Column#30)->Column#27 | 17.3 KB | N/A || └─TableReader_47 | 1.00 | 3 | root | | time:3.8s, loops:2, cop_task: {num: 6, max: 0s, min: 0s, avg: 0s, p95: 0s, copr_cache_hit_ratio: 0.00} | data:ExchangeSender_46 | N/A | N/A || └─ExchangeSender_46 | 1.00 | 3 | mpp[tiflash] | | tiflash_task:{proc max:3.79s, min:3.78s, avg: 3.78s, p80:3.79s, p95:3.79s, iters:3, tasks:3, threads:60} | ExchangeType: PassThrough | N/A | N/A || └─HashAgg_13 | 1.00 | 3 | mpp[tiflash] | | tiflash_task:{proc max:3.79s, min:3.78s, avg: 3.78s, p80:3.79s, p95:3.79s, iters:3, tasks:3, threads:60} | funcs:max(tpch_100.lineitem.l_shipdate)->Column#28, funcs:max(tpch_100.lineitem.l_commitdate)->Column#29, funcs:max(tpch_100.lineitem.l_receiptdate)->Column#30 | N/A | N/A || ├─ExchangeReceiver_30(Build) | 1000000.00 | 1000000 | mpp[tiflash] | | tiflash_task:{proc max:23.3ms, min:21ms, avg: 22.5ms, p80:23.3ms, p95:23.3ms, iters:120, tasks:3, threads:60} | stream_count: 20 | N/A | N/A || │ └─ExchangeSender_29 | 1000000.00 | 1000000 | mpp[tiflash] | | tiflash_task:{proc max:22.7ms, min:0s, avg: 7.57ms, p80:22.7ms, p95:22.7ms, iters:16, tasks:3, threads:2} | ExchangeType: HashPartition, Hash Cols: [name: tpch_100.supplier.s_suppkey, collate: binary], stream_count: 20 | N/A | N/A || └─ExchangeReceiver_33(Probe) | 600037902.00 | 600037902 | mpp[tiflash] | | tiflash_task:{proc max:564.3ms, min:340ms, avg: 438.5ms, p80:564.3ms, p95:564.3ms, iters:27583, tasks:3, threads:60} | | N/A | N/A || └─ExchangeSender_32 | 600037902.00 | 600037902 | mpp[tiflash] | | tiflash_task:{proc max:3.69s, min:0s, avg: 1.23s, p80:3.69s, p95:3.69s, iters:9298, tasks:3, threads:60} | ExchangeType: HashPartition, Hash Cols: [name: tpch_100.lineitem.l_suppkey, collate: binary] | N/A | N/A || └─TableFullScan_31 | 600037902.00 | 600037902 | mpp[tiflash] | table:lineitem | tiflash_task:{proc max:62.8ms, min:0s, avg: 20.9ms, p80:62.8ms, p95:62.8ms, iters:9298, tasks:3, threads:60}, tiflash_scan:{dtfile:{total_scanned_packs:73465, total_skipped_packs:13060, total_scanned_rows:600168663, total_skipped_rows:106699256, total_rs_index_load_time: 16ms, total_read_time: 27979ms}, total_create_snapshot_time: 0ms} | keep order:false | N/A | N/A |+------------------------------------------+--------------+-----------+--------------+----------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------+---------+------+11 rows in set (3.83 sec)
设置 tidb_broadcast_join_threshold_size：
mysql> set @@tidb_broadcast_join_threshold_size = 10000000;Query OK, 0 rows affected (0.00 sec)
tidb_broadcast_join_threshold_size 设置后：
设置更大的执行并发度
设置更大的执行并发度，可以让 TiFlash 占用更多系统 CPU 资源，从而提升查询性能。
，单位为线程。用来设置 TiFlash 中 request 执行的最大并发度。
set @@tidb_max_tiflash_threads = 20;
在以下示例中，tidb_max_tiflash_threads 设置前，所有 TiFlash 的算子的执行线程数为 24。tidb_max_tiflash_threads 设置后，所有 TiFlash 的算子的执行线程数为 60。
tidb_max_tiflash_threads 设置前：
mysql> explain analyze select a, count(*) from t group by a;+--------------------------------------+--------------+-----------+--------------+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------+--------+------+| id | estRows | actRows | task | access object | execution info | operator info | memory | disk |+--------------------------------------+--------------+-----------+--------------+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------+--------+------+| TableReader_44 | 20.00 | 20 | root | | time:655.9ms, loops:2, cop_task: {num: 14, max: 0s, min: 0s, avg: 0s, p95: 0s, copr_cache_hit_ratio: 0.00} | data:ExchangeSender_43 | N/A | N/A || └─ExchangeSender_43 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:654.6ms, min:652.4ms, avg: 653.8ms, p80:654.6ms, p95:654.6ms, iters:11, tasks:3, threads:24} | ExchangeType: PassThrough | N/A | N/A || └─Projection_5 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:654.3ms, min:651.4ms, avg: 653.1ms, p80:654.3ms, p95:654.3ms, iters:11, tasks:3, threads:24} | test.t.a, Column#22 | N/A | N/A || └─Projection_39 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:654.3ms, min:651.4ms, avg: 653.1ms, p80:654.3ms, p95:654.3ms, iters:11, tasks:3, threads:24} | Column#22, test.t.a | N/A | N/A || └─HashAgg_40 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:654.3ms, min:651.4ms, avg: 653.1ms, p80:654.3ms, p95:654.3ms, iters:11, tasks:3, threads:24} | group by:test.t.a, funcs:sum(Column#29)->Column#22, funcs:firstrow(test.t.a)->test.t.a, stream_count: 8 | N/A | N/A || └─ExchangeReceiver_42 | 20.00 | 60 | mpp[tiflash] | | tiflash_task:{proc max:654.3ms, min:651.4ms, avg: 653.1ms, p80:654.3ms, p95:654.3ms, iters:11, tasks:3, threads:24} | stream_count: 8 | N/A | N/A || └─ExchangeSender_41 | 20.00 | 60 | mpp[tiflash] | | tiflash_task:{proc max:649ms, min:0s, avg: 216.3ms, p80:649ms, p95:649ms, iters:3, tasks:3, threads:24} | ExchangeType: HashPartition, Hash Cols: [name: test.t.a, collate: binary], stream_count: 8 | N/A | N/A || └─HashAgg_37 | 20.00 | 60 | mpp[tiflash] | | tiflash_task:{proc max:649ms, min:0s, avg: 216.3ms, p80:649ms, p95:649ms, iters:3, tasks:3, threads:24} | group by:test.t.a, funcs:count(1)->Column#29 | N/A | N/A || └─TableFullScan_26 | 600000000.00 | 600000000 | mpp[tiflash] | table:t | tiflash_task:{proc max:40ms, min:0s, avg: 13.3ms, p80:40ms, p95:40ms, iters:9386, tasks:3, threads:24}, tiflash_scan:{dtfile:{total_scanned_packs:73833, total_skipped_packs:174, total_scanned_rows:600000000, total_skipped_rows:1402537, total_rs_index_load_time: 0ms, total_read_time: 4ms}, total_create_snapshot_time: 0ms} | keep order:false | N/A | N/A |+--------------------------------------+--------------+-----------+--------------+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------+--------+------+9 rows in set (0.67 sec)
设置 tidb_max_tiflash_threads：
mysql> set @@tidb_max_tiflash_threads = 20;Query OK, 0 rows affected (0.00 sec)
tidb_max_tiflash_threads 设置后：
mysql> explain analyze select a, count(*) from t group by a;+--------------------------------------+--------------+-----------+--------------+---------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------+--------+------+| id | estRows | actRows | task | access object | execution info | operator info | memory | disk |+--------------------------------------+--------------+-----------+--------------+---------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------+--------+------+| TableReader_44 | 20.00 | 20 | root | | time:357.7ms, loops:2, cop_task: {num: 19, max: 0s, min: 0s, avg: 0s, p95: 0s, copr_cache_hit_ratio: 0.00} | data:ExchangeSender_43 | N/A | N/A || └─ExchangeSender_43 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:355.3ms, min:354.6ms, avg: 355ms, p80:355.3ms, p95:355.3ms, iters:16, tasks:3, threads:60} | ExchangeType: PassThrough | N/A | N/A || └─Projection_5 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:354.3ms, min:353.6ms, avg: 354ms, p80:354.3ms, p95:354.3ms, iters:16, tasks:3, threads:60} | test.t.a, Column#22 | N/A | N/A || └─Projection_39 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:354.3ms, min:353.6ms, avg: 354ms, p80:354.3ms, p95:354.3ms, iters:16, tasks:3, threads:60} | Column#22, test.t.a | N/A | N/A || └─HashAgg_40 | 20.00 | 20 | mpp[tiflash] | | tiflash_task:{proc max:354.3ms, min:353.6ms, avg: 354ms, p80:354.3ms, p95:354.3ms, iters:16, tasks:3, threads:60} | group by:test.t.a, funcs:sum(Column#29)->Column#22, funcs:firstrow(test.t.a)->test.t.a, stream_count: 20 | N/A | N/A || └─ExchangeReceiver_42 | 20.00 | 60 | mpp[tiflash] | | tiflash_task:{proc max:354.3ms, min:353.6ms, avg: 354ms, p80:354.3ms, p95:354.3ms, iters:16, tasks:3, threads:60} | stream_count: 20 | N/A | N/A || └─ExchangeSender_41 | 20.00 | 60 | mpp[tiflash] | | tiflash_task:{proc max:349.6ms, min:0s, avg: 116.5ms, p80:349.6ms, p95:349.6ms, iters:3, tasks:3, threads:60} | ExchangeType: HashPartition, Hash Cols: [name: test.t.a, collate: binary], stream_count: 20 | N/A | N/A || └─HashAgg_37 | 20.00 | 60 | mpp[tiflash] | | tiflash_task:{proc max:347.6ms, min:0s, avg: 115.9ms, p80:347.6ms, p95:347.6ms, iters:3, tasks:3, threads:60} | group by:test.t.a, funcs:count(1)->Column#29 | N/A | N/A || └─TableFullScan_26 | 600000000.00 | 600000000 | mpp[tiflash] | table:t | tiflash_task:{proc max:36.6ms, min:0s, avg: 12.2ms, p80:36.6ms, p95:36.6ms, iters:9389, tasks:3, threads:60}, tiflash_scan:{dtfile:{total_scanned_packs:73833, total_skipped_packs:418, total_scanned_rows:600001386, total_skipped_rows:3381854, total_rs_index_load_time: 10ms, total_read_time: 61ms}, total_create_snapshot_time: 0ms} | keep order:false | N/A | N/A |+--------------------------------------+--------------+-----------+--------------+---------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------+--------+------+9 rows in set (0.37 sec)
细粒度 Shuffle 可以通过参数增加窗口函数执行的并发度，让函数执行占用更多系统资源，从而提升查询性能。
，单位为线程数。当窗口函数下推到 TiFlash 执行时，可以通过该变量控制窗口函数执行的并行度。
set @@tiflash_fine_grained_shuffle_stream_count = 20;
在以下示例中，tiflash_fine_grained_shuffle_stream_count 设置前，[ExchangeSender_11, ExchangeReceiver_12, Sort_13, Window_22] 的 stream_count 是 8。tiflash_fine_grained_shuffle_stream_count 设置后，[ExchangeSender_11, ExchangeReceiver_12, Sort_13, Window_22] 的 stream_count 是 20。
tiflash_fine_grained_shuffle_stream_count 设置前：
mysql> explain analyze select *, row_number() over (partition by a) from t;+----------------------------------+--------------+-----------+--------------+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------+--------+------+| id | estRows | actRows | task | access object | execution info | operator info | memory | disk |+----------------------------------+--------------+-----------+--------------+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------+--------+------+| TableReader_24 | 600000000.00 | 600000000 | root | | time:4m30.5s, loops:585941, cop_task: {num: 9163, max: 0s, min: 0s, avg: 0s, p95: 0s, copr_cache_hit_ratio: 0.00} | data:ExchangeSender_23 | N/A | N/A || └─ExchangeSender_23 | 600000000.00 | 600000000 | mpp[tiflash] | | tiflash_task:{proc max:4m30.5s, min:3m4.8s, avg: 3m36.1s, p80:4m30.5s, p95:4m30.5s, iters:9160, tasks:3, threads:24} | ExchangeType: PassThrough | N/A | N/A || └─Window_22 | 600000000.00 | 600000000 | mpp[tiflash] | | tiflash_task:{proc max:3m31.6s, min:2m26.2s, avg: 2m50.7s, p80:3m31.6s, p95:3m31.6s, iters:9160, tasks:3, threads:24} | row_number()->Column#23 over(partition by test.t.a rows between current row and current row), stream_count: 8 | N/A | N/A || └─Sort_13 | 600000000.00 | 600000000 | mpp[tiflash] | | tiflash_task:{proc max:3m28.6s, min:2m24.2s, avg: 2m48.4s, p80:3m28.6s, p95:3m28.6s, iters:9160, tasks:3, threads:24} | test.t.a, stream_count: 8 | N/A | N/A || └─ExchangeReceiver_12 | 600000000.00 | 600000000 | mpp[tiflash] | | tiflash_task:{proc max:32.4s, min:32s, avg: 32.1s, p80:32.4s, p95:32.4s, iters:49307, tasks:3, threads:24} | stream_count: 8 | N/A | N/A || └─ExchangeSender_11 | 600000000.00 | 600000000 | mpp[tiflash] | | tiflash_task:{proc max:32s, min:0s, avg: 10.7s, p80:32s, p95:32s, iters:9386, tasks:3, threads:60} | ExchangeType: HashPartition, Hash Cols: [name: test.t.a, collate: binary], stream_count: 8 | N/A | N/A || └─TableFullScan_10 | 600000000.00 | 600000000 | mpp[tiflash] | table:t | tiflash_task:{proc max:113.9ms, min:0s, avg: 38ms, p80:113.9ms, p95:113.9ms, iters:9386, tasks:3, threads:60}, tiflash_scan:{dtfile:{total_scanned_packs:73834, total_skipped_packs:190, total_scanned_rows:600000000, total_skipped_rows:1536382, total_rs_index_load_time: 16ms, total_read_time: 166324ms}, total_create_snapshot_time: 0ms} | keep order:false | N/A | N/A |+----------------------------------+--------------+-----------+--------------+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------+--------+------+7 rows in set (4 min 30.59 sec)
mysql> set @@tiflash_fine_grained_shuffle_stream_count = 20;Query OK, 0 rows affected (0.00 sec)
tiflash_fine_grained_shuffle_stream_count 设置后：
mysql> explain analyze select *, row_number() over (partition by a) from t;+----------------------------------+--------------+-----------+--------------+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------+--------+------+| id | estRows | actRows | task | access object | execution info | operator info | memory | disk |+----------------------------------+--------------+-----------+--------------+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------+--------+------+| TableReader_24 | 600000000.00 | 600000000 | root | | time:2m55s, loops:585941, cop_task: {num: 9163, max: 0s, min: 0s, avg: 0s, p95: 0s, copr_cache_hit_ratio: 0.00} | data:ExchangeSender_23 | N/A | N/A || └─ExchangeSender_23 | 600000000.00 | 600000000 | mpp[tiflash] | | tiflash_task:{proc max:2m55s, min:1m37s, avg: 2m28.7s, p80:2m55s, p95:2m55s, iters:9160, tasks:3, threads:60} | ExchangeType: PassThrough | N/A | N/A || └─Window_22 | 600000000.00 | 600000000 | mpp[tiflash] | | tiflash_task:{proc max:2m12.9s, min:1m17s, avg: 1m54.2s, p80:2m12.9s, p95:2m12.9s, iters:9160, tasks:3, threads:60} | row_number()->Column#23 over(partition by test.t.a rows between current row and current row), stream_count: 20 | N/A | N/A || └─Sort_13 | 600000000.00 | 600000000 | mpp[tiflash] | | tiflash_task:{proc max:2m10.9s, min:1m16s, avg: 1m52.5s, p80:2m10.9s, p95:2m10.9s, iters:9160, tasks:3, threads:60} | test.t.a, stream_count: 20 | N/A | N/A || └─ExchangeReceiver_12 | 600000000.00 | 600000000 | mpp[tiflash] | | tiflash_task:{proc max:27.2s, min:25.5s, avg: 26.6s, p80:27.2s, p95:27.2s, iters:49602, tasks:3, threads:60} | stream_count: 20 | N/A | N/A || └─ExchangeSender_11 | 600000000.00 | 600000000 | mpp[tiflash] | | tiflash_task:{proc max:25.5s, min:0s, avg: 8.51s, p80:25.5s, p95:25.5s, iters:9388, tasks:3, threads:60} | ExchangeType: HashPartition, Hash Cols: [name: test.t.a, collate: binary], stream_count: 20 | N/A | N/A || └─TableFullScan_10 | 600000000.00 | 600000000 | mpp[tiflash] | table:t | tiflash_task:{proc max:167.3ms, min:0s, avg: 55.8ms, p80:167.3ms, p95:167.3ms, iters:9388, tasks:3, threads:60}, tiflash_scan:{dtfile:{total_scanned_packs:73834, total_skipped_packs:408, total_scanned_rows:600002896, total_skipped_rows:3307316, total_rs_index_load_time: 20ms, total_read_time: 179431ms}, total_create_snapshot_time: 0ms} | keep order:false | N/A | N/A |7 rows in set (2 min 55.09 sec)
