Skew Hints

Function

Theses hints specify redistribution keys containing skew data and skew values, and are used to optimize redistribution involving Join or HashAgg.

Precautions

• Skew hints are used only if redistribution is required and the specified skew information matches the redistribution information.
• Skew hints are controlled by the GUC parameter skew_option. If the parameter is disabled, skew hints cannot be used for solving skew.
• Currently, skew hints support only the table relationships of the ordinary table and subquery types. Hints can be specified for base tables, subqueries, and WITH ... AS clauses. Unlike other hints, a subquery can be used in skew hints regardless of whether it is pulled up.
• Use an alias (if any) to specify a table where data skew occurs.
• You can use a name or an alias to specify a skew column as long as it is not ambiguous. The columns in skew hints cannot be expressions. If data skew occurs in the redistribution that uses an expression as a redistribution key, set the redistribution key as a new column and specify the column in skew hints.
• The number of skew values must be an integer multiple of the number of columns. Skew values must be grouped based on the column sequence, with each group containing a maximum of 10 values. You can specify duplicate values to group skew columns having different number of skew values. For example, the c1 and c2 columns of the t1 table contains skew data. The skew value of the c1 column is a1, and the skew values of the c2 column are b1 and b2. In this case, the skew hint is skew(t1 (c1 c2) ((a1 b1)(a1 b2))). (a1 b1) is a value group, where NULL is allowed as a skew value. Each hint can contain a maximum of 10 groups and the number of groups should be an integer multiple of the number of columns.
• In the redistribution optimization of Join, a skew value must be specified for skew hints. The skew value can be left empty for HashAgg.
• If multiple tables, columns, or values are specified, separate items of the same type with spaces.
• The type of skew values cannot be forcibly converted in hints. To specify a string, enclose it with single quotation marks (' ').

Syntax

• Specify single-table skew.

  1	skew([@block_name] table (column) [(value)])

• Specify intermediate result skew.

  1	skew([@block_name] (join_rel) (column) [(value)])

Parameter Description

• block_name indicates the block name of the statement block. For details, see block_name.
• table specifies the table where skew occurs.
  

  • The syntax format of the table is as follows:

    [schema.]table[@block_name]

    The table name can contain the schema name or block name before the subquery statement block is promoted. If the subquery statement block is optimized and rewritten by the optimizer, the value of block_name is different from that of block_name in leading.

  • If a table has an alias, the alias is preferentially used to represent the table.
• join_rel specifies two or more joined tables. For example, (t1 t2) indicates that the result of joining t1 and t2 tables contains skew data.
• column specifies one or more columns where skew occurs.
• value specifies one or more skew values.

Suggestion

• For a multi-level query, write the hint on the layer where data skew occurs.
• For a listed subquery, you can specify the subquery name in a hint. If you know data skew occurs on which base table, directly specify the table.
• Aliases are preferred when you specify a table or column in a hint.

Examples

Specify single-table skew.

• Specify hints in the original query.

  For example, the original query is as follows:

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

  explain with customer_total_return as (select sr_customer_sk as ctr_customer_sk ,sr_store_sk as ctr_store_sk ,sum(SR_FEE) as ctr_total_return from store_returns ,date_dim where sr_returned_date_sk = d_date_sk and d_year =2000 group by sr_customer_sk ,sr_store_sk) select c_customer_id from customer_total_return ctr1 ,store ,customer where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2 from customer_total_return ctr2 where ctr1.ctr_store_sk = ctr2.ctr_store_sk) and s_store_sk = ctr1.ctr_store_sk and s_state = 'NM' and ctr1.ctr_customer_sk = c_customer_sk order by c_customer_id limit 100;

  

  Specify the hints of HashAgg in the inner with clause and of the outer Hash Join. The query containing hints is as follows:

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

  explain with customer_total_return as (select /*+ skew(store_returns(sr_store_sk sr_customer_sk)) */sr_customer_sk as ctr_customer_sk ,sr_store_sk as ctr_store_sk ,sum(SR_FEE) as ctr_total_return from store_returns ,date_dim where sr_returned_date_sk = d_date_sk and d_year =2000 group by sr_customer_sk ,sr_store_sk) select /*+ skew(ctr1(ctr_customer_sk)(11))*/ c_customer_id from customer_total_return ctr1 ,store ,customer where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2 from customer_total_return ctr2 where ctr1.ctr_store_sk = ctr2.ctr_store_sk) and s_store_sk = ctr1.ctr_store_sk and s_state = 'NM' and ctr1.ctr_customer_sk = c_customer_sk order by c_customer_id limit 100;

  The hints indicate that the group by in the inner with clause contains skew data during redistribution by HashAgg, corresponding to the original Hash Agg operators 10 and 21; and that the ctr_customer_sk column in the outer ctr1 table contains skew data during redistribution by Hash Join, corresponding to operator 6 in the original plan. The optimized plan is as follows:

  

  To solve data skew in the redistribution, Hash Agg is changed to double-level Agg operators and the redistribution operators used by Hash Join are changed in the optimized plan.