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Push-down Calculations Supported by TiFlash

This document introduces the push-down calculations supported by TiFlash.

Push-down operators

TiFlash supports the push-down of the following operators:

  • TableScan: Reads data from tables.
  • Selection: Filters data.
  • HashAgg: Performs data aggregation based on the Hash Aggregation algorithm.
  • StreamAgg: Performs data aggregation based on the Stream Aggregation algorithm. SteamAgg only supports the aggregation without the GROUP BY condition.
  • TopN: Performs the TopN calculation.
  • Limit: Performs the limit calculation.
  • Project: Performs the projection calculation.
  • HashJoin: Performs the join calculation using the Hash Join algorithm, but with the following conditions:
    • The operator can be pushed down only in the MPP mode.
    • Supported joins are Inner Join, Left Join, Semi Join, Anti Semi Join, Left Semi Join, and Anti Left Semi Join.
    • The preceding joins support both Equi Join and Non-Equi Join (Cartesian Join or Null-aware Semi Join). When calculating Cartesian Join or Null-aware Semi Join, the Broadcast algorithm, instead of the Shuffle Hash Join algorithm, is used.
  • Window functions: Currently, TiFlash supports ROW_NUMBER(), RANK(), DENSE_RANK(), LEAD(), LAG(), FIRST_VALUE(), and LAST_VALUE().

In TiDB, operators are organized in a tree structure. For an operator to be pushed down to TiFlash, all of the following prerequisites must be met:

  • All of its child operators can be pushed down to TiFlash.
  • If an operator contains expressions (most of the operators contain expressions), all expressions of the operator can be pushed down to TiFlash.

Push-down expressions

TiFlash supports the following push-down expressions:

Expression TypeOperations
Numeric functions and operators+, -, /, *, %, >=, <=, =, !=, <, >, ROUND(), ABS(), FLOOR(int), CEIL(int), CEILING(int), SQRT(), LOG(), LOG2(), LOG10(), LN(), EXP(), POW(), POWER(), SIGN(), RADIANS(), DEGREES(), CONV(), CRC32(), GREATEST(int/real), LEAST(int/real)
Logical functions and operatorsAND, OR, NOT, CASE WHEN, IF(), IFNULL(), ISNULL(), IN, LIKE, ILIKE, COALESCE, IS
Bitwise operations& (bitand), | (bitor), ~ (bitneg), ^ (bitxor)
String functionsSUBSTR(), CHAR_LENGTH(), REPLACE(), CONCAT(), CONCAT_WS(), LEFT(), RIGHT(), ASCII(), LENGTH(), TRIM(), LTRIM(), RTRIM(), POSITION(), FORMAT(), LOWER(), UCASE(), UPPER(), SUBSTRING_INDEX(), LPAD(), RPAD(), STRCMP()
Regular expression functions and operatorsREGEXP, REGEXP_LIKE(), REGEXP_INSTR(), REGEXP_SUBSTR(), REGEXP_REPLACE(), RLIKE
Date functionsDATE_FORMAT(), TIMESTAMPDIFF(), FROM_UNIXTIME(), UNIX_TIMESTAMP(int), UNIX_TIMESTAMP(decimal), STR_TO_DATE(date), STR_TO_DATE(datetime), DATEDIFF(), YEAR(), MONTH(), DAY(), EXTRACT(datetime), DATE(), HOUR(), MICROSECOND(), MINUTE(), SECOND(), SYSDATE(), DATE_ADD/ADDDATE(datetime, int), DATE_ADD/ADDDATE(string, int/real), DATE_SUB/SUBDATE(datetime, int), DATE_SUB/SUBDATE(string, int/real), QUARTER(), DAYNAME(), DAYOFMONTH(), DAYOFWEEK(), DAYOFYEAR(), LAST_DAY(), MONTHNAME(), TO_SECONDS(), TO_DAYS(), FROM_DAYS(), WEEKOFYEAR()
JSON functionJSON_LENGTH(), ->, ->>, JSON_EXTRACT(), JSON_ARRAY(), JSON_DEPTH(), JSON_VALID(), JSON_KEYS(), JSON_CONTAINS_PATH(), JSON_UNQUOTE()
Conversion functionsCAST(int AS DOUBLE), CAST(int AS DECIMAL), CAST(int AS STRING), CAST(int AS TIME), CAST(double AS INT), CAST(double AS DECIMAL), CAST(double AS STRING), CAST(double AS TIME), CAST(string AS INT), CAST(string AS DOUBLE), CAST(string AS DECIMAL), CAST(string AS TIME), CAST(decimal AS INT), CAST(decimal AS STRING), CAST(decimal AS TIME), CAST(decimal AS DOUBLE), CAST(time AS INT), CAST(time AS DECIMAL), CAST(time AS STRING), CAST(time AS REAL), CAST(json AS JSON), CAST(json AS STRING), CAST(int AS JSON), CAST(real AS JSON), CAST(decimal AS JSON), CAST(string AS JSON), CAST(time AS JSON), CAST(duration AS JSON)
Aggregate functionsMIN(), MAX(), SUM(), COUNT(), AVG(), APPROX_COUNT_DISTINCT(), GROUP_CONCAT()
Miscellaneous functionsINET_NTOA(), INET_ATON(), INET6_NTOA(), INET6_ATON()

Restrictions

  • Expressions that contain the Bit, Set, and Geometry types cannot be pushed down to TiFlash.

  • The DATE_ADD(), DATE_SUB(), ADDDATE(), and SUBDATE() functions support the following interval types only. If other interval types are used, TiFlash reports errors.

    • DAY
    • WEEK
    • MONTH
    • YEAR
    • HOUR
    • MINUTE
    • SECOND

If a query encounters unsupported push-down calculations, TiDB needs to complete the remaining calculations, which might greatly affect the TiFlash acceleration effect. The currently unsupported operators and expressions might be supported in future versions.

Functions like MAX() are supported for push-down when used as aggregate functions, but not as window functions.

Examples

This section provides some examples of pushing down operators and expressions to TiFlash.

Example 1: Push operators down to TiFlash

CREATE TABLE t(id INT PRIMARY KEY, a INT);
ALTER TABLE t SET TIFLASH REPLICA 1;

EXPLAIN SELECT * FROM t LIMIT 3;

+------------------------------+---------+--------------+---------------+--------------------------------+
| id                           | estRows | task         | access object | operator info                  |
+------------------------------+---------+--------------+---------------+--------------------------------+
| Limit_9                      | 3.00    | root         |               | offset:0, count:3              |
| └─TableReader_17             | 3.00    | root         |               | data:ExchangeSender_16         |
|   └─ExchangeSender_16        | 3.00    | mpp[tiflash] |               | ExchangeType: PassThrough      |
|     └─Limit_15               | 3.00    | mpp[tiflash] |               | offset:0, count:3              |
|       └─TableFullScan_14     | 3.00    | mpp[tiflash] | table:t       | keep order:false, stats:pseudo |
+------------------------------+---------+--------------+---------------+--------------------------------+
5 rows in set (0.18 sec)

In the preceding example, the operator Limit is pushed down to TiFlash for filtering data, which helps reduce the amount of data to be transferred over the network and reduce the network overhead. This is indicated by the mpp[tiflash] value of the task column on the row of the Limit_15 operator.

Example 2: Push expressions down to TiFlash

CREATE TABLE t(id INT PRIMARY KEY, a INT);
ALTER TABLE t SET TIFLASH REPLICA 1;
INSERT INTO t(id,a) VALUES (1,2),(2,4),(11,2),(12,4),(13,4),(14,7);

EXPLAIN SELECT MAX(id + a) FROM t GROUP BY a;

+------------------------------------+---------+--------------+---------------+---------------------------------------------------------------------------+
| id                                 | estRows | task         | access object | operator info                                                             |
+------------------------------------+---------+--------------+---------------+---------------------------------------------------------------------------+
| TableReader_45                     | 4.80    | root         |               | data:ExchangeSender_44                                                    |
| └─ExchangeSender_44                | 4.80    | mpp[tiflash] |               | ExchangeType: PassThrough                                                 |
|   └─Projection_39                  | 4.80    | mpp[tiflash] |               | Column#3                                                                  |
|     └─HashAgg_37                   | 4.80    | mpp[tiflash] |               | group by:Column#9, funcs:max(Column#8)->Column#3                          |
|       └─Projection_46              | 6.00    | mpp[tiflash] |               | plus(test.t.id, test.t.a)->Column#8, test.t.a                             |
|         └─ExchangeReceiver_23      | 6.00    | mpp[tiflash] |               |                                                                           |
|           └─ExchangeSender_22      | 6.00    | mpp[tiflash] |               | ExchangeType: HashPartition, Hash Cols: [name: test.t.a, collate: binary] |
|             └─TableFullScan_21     | 6.00    | mpp[tiflash] | table:t       | keep order:false, stats:pseudo                                            |
+------------------------------------+---------+--------------+---------------+---------------------------------------------------------------------------+
8 rows in set (0.18 sec)

In the preceding example, the expression id + a is pushed down to TiFlash for calculation in advance. This helps reduce the amount of data to be transferred over the network, thus reducing the network transmission overhead and improving the overall calculation performance. This is indicated by the mpp[tiflash] value in the task column of the row where the operator column has the plus(test.t.id, test.t.a) value.

Example 3: Restrictions for pushdown

CREATE TABLE t(id INT PRIMARY KEY, a INT);
ALTER TABLE t SET TIFLASH REPLICA 1;
INSERT INTO t(id,a) VALUES (1,2),(2,4),(11,2),(12,4),(13,4),(14,7);

EXPLAIN SELECT id FROM t WHERE TIME(now()+ a) < '12:00:00';

+-----------------------------+---------+--------------+---------------+--------------------------------------------------------------------------------------------------+
| id                          | estRows | task         | access object | operator info                                                                                    |
+-----------------------------+---------+--------------+---------------+--------------------------------------------------------------------------------------------------+
| Projection_4                | 4.80    | root         |               | test.t.id                                                                                        |
| └─Selection_6               | 4.80    | root         |               | lt(cast(time(cast(plus(20230110083056, test.t.a), var_string(20))), var_string(10)), "12:00:00") |
|   └─TableReader_11          | 6.00    | root         |               | data:ExchangeSender_10                                                                           |
|     └─ExchangeSender_10     | 6.00    | mpp[tiflash] |               | ExchangeType: PassThrough                                                                        |
|       └─TableFullScan_9     | 6.00    | mpp[tiflash] | table:t       | keep order:false, stats:pseudo                                                                   |
+-----------------------------+---------+--------------+---------------+--------------------------------------------------------------------------------------------------+
5 rows in set, 3 warnings (0.20 sec)

The preceding example only performs TableFullScan on TiFlash. Other functions are calculated and filtered on root and are not pushed down to TiFlash.

You can identify the operators and expressions that cannot be pushed down to TiFlash by running the following command:

SHOW WARNINGS;

+---------+------+------------------------------------------------------------------------------------------------------------------------------------+
| Level   | Code | Message                                                                                                                            |
+---------+------+------------------------------------------------------------------------------------------------------------------------------------+
| Warning | 1105 | Scalar function 'time'(signature: Time, return type: time) is not supported to push down to storage layer now.                     |
| Warning | 1105 | Scalar function 'cast'(signature: CastDurationAsString, return type: var_string(10)) is not supported to push down to tiflash now. |
| Warning | 1105 | Scalar function 'cast'(signature: CastDurationAsString, return type: var_string(10)) is not supported to push down to tiflash now. |
+---------+------+------------------------------------------------------------------------------------------------------------------------------------+
3 rows in set (0.18 sec)

The expressions in the preceding example cannot be completely pushed down to TiFlash, because the functions Time and Cast cannot be pushed down to TiFlash.

Example 4: Window functions

CREATE TABLE t(id INT PRIMARY KEY, c1 VARCHAR(100));
ALTER TABLE t SET TIFLASH REPLICA 1;
INSERT INTO t VALUES(1,"foo"),(2,"bar"),(3,"bar foo"),(10,"foo"),(20,"bar"),(30,"bar foo");

EXPLAIN SELECT id, ROW_NUMBER() OVER (PARTITION BY id > 10) FROM t;
+----------------------------------+----------+--------------+---------------+---------------------------------------------------------------------------------------------------------------+
| id                               | estRows  | task         | access object | operator info                                                                                                 |
+----------------------------------+----------+--------------+---------------+---------------------------------------------------------------------------------------------------------------+
| TableReader_30                   | 10000.00 | root         |               | MppVersion: 1, data:ExchangeSender_29                                                                         |
| └─ExchangeSender_29              | 10000.00 | mpp[tiflash] |               | ExchangeType: PassThrough                                                                                     |
|   └─Projection_7                 | 10000.00 | mpp[tiflash] |               | test.t.id, Column#5, stream_count: 4                                                                          |
|     └─Window_28                  | 10000.00 | mpp[tiflash] |               | row_number()->Column#5 over(partition by Column#4 rows between current row and current row), stream_count: 4  |
|       └─Sort_14                  | 10000.00 | mpp[tiflash] |               | Column#4, stream_count: 4                                                                                     |
|         └─ExchangeReceiver_13    | 10000.00 | mpp[tiflash] |               | stream_count: 4                                                                                               |
|           └─ExchangeSender_12    | 10000.00 | mpp[tiflash] |               | ExchangeType: HashPartition, Compression: FAST, Hash Cols: [name: Column#4, collate: binary], stream_count: 4 |
|             └─Projection_10      | 10000.00 | mpp[tiflash] |               | test.t.id, gt(test.t.id, 10)->Column#4                                                                        |
|               └─TableFullScan_11 | 10000.00 | mpp[tiflash] | table:t       | keep order:false, stats:pseudo                                                                                |
+----------------------------------+----------+--------------+---------------+---------------------------------------------------------------------------------------------------------------+
9 rows in set (0.0073 sec)

In this output, you can see that the Window operation has a value of mpp[tiflash] in the task column, indicating that the ROW_NUMBER() OVER (PARTITION BY id > 10) operation can be pushed down to TiFlash.

CREATE TABLE t(id INT PRIMARY KEY, c1 VARCHAR(100));
ALTER TABLE t SET TIFLASH REPLICA 1;
INSERT INTO t VALUES(1,"foo"),(2,"bar"),(3,"bar foo"),(10,"foo"),(20,"bar"),(30,"bar foo");

EXPLAIN SELECT id, MAX(id) OVER (PARTITION BY id > 10) FROM t;
+-----------------------------+----------+-----------+---------------+------------------------------------------------------------+
| id                          | estRows  | task      | access object | operator info                                              |
+-----------------------------+----------+-----------+---------------+------------------------------------------------------------+
| Projection_6                | 10000.00 | root      |               | test.t1.id, Column#5                                       |
| └─Shuffle_14                | 10000.00 | root      |               | execution info: concurrency:5, data sources:[Projection_8] |
|   └─Window_7                | 10000.00 | root      |               | max(test.t1.id)->Column#5 over(partition by Column#4)      |
|     └─Sort_13               | 10000.00 | root      |               | Column#4                                                   |
|       └─Projection_8        | 10000.00 | root      |               | test.t1.id, gt(test.t1.id, 10)->Column#4                   |
|         └─TableReader_10    | 10000.00 | root      |               | data:TableFullScan_9                                       |
|           └─TableFullScan_9 | 10000.00 | cop[tikv] | table:t1      | keep order:false, stats:pseudo                             |
+-----------------------------+----------+-----------+---------------+------------------------------------------------------------+
7 rows in set (0.0010 sec)

In this output, you can see that the Window operation has a value of root in the task column, indicating that the MAX(id) OVER (PARTITION BY id > 10) operation cannot be pushed down to TiFlash. This is because MAX() is only supported for push-down as an aggregate function and not as a window function.

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