Project: Flink (App Definition and Development / Streaming & Messaging)
File: group-by.md

title: "Group By" weight: 3 type: docs <!-- Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. The ASF licenses this file to you under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. --> The `Group by` clause is used to compute a single result from multiple input rows with given aggregation function. Hive dialect also supports enhanced aggregation features to do multiple aggregations based on the same record by using `ROLLUP`/`CUBE`/`GROUPING SETS`. ```sql groupbyclause: groupbyclause1 | groupbyclause2 groupbyclause_1: GROUP BY group_expression [ , ... ] [ WITH ROLLUP | WITH CUBE ] groupbyclause_2: GROUP BY { groupexpression | { ROLLUP | CUBE | GROUPING SETS } ( groupingset [ , ... ] ) } [ , ... ] grouping_set: { expression | ( [ expression [ , ... ] ] ) } groupByQuery: SELECT expression [ , ... ] FROM src groupByClause? ``` In `group_expression`, columns can be also specified by position number. But please remember: For Hive 0.11.0 through 2.1.x, set `hive.groupby.orderby.position.alias` to true (the default is false) For Hive 2.2.0 and later, set `hive.groupby.position.alias` to true (the default is false) `GROUPING SETS` allow for more complex grouping operations than those describable by a standard `GROUP BY`. Rows are grouped separately by each specified grouping set and aggregates are computed for each group just as for simple `GROUP BY` clauses. All `GROUPING SET` clauses can be logically expressed in terms of several `GROUP BY` queries connected by

For example: ```sql SELECT a, b, SUM( c ) FROM tab1 GROUP BY a, b GROUPING SETS ( (a, b), a, b, ( ) ) ``` is equivalent to ```sql SELECT a, b, SUM( c ) FROM tab1 GROUP BY a, b UNION SELECT a, null, SUM( c ) FROM tab1 GROUP BY a, null UNION SELECT null, b, SUM( c ) FROM tab1 GROUP BY null, b UNION SELECT null, null, SUM( c ) FROM tab1 ``` When aggregates are displayed for a column its value is null. This may conflict in case the column itself has some null values. There needs to be some way to identify NULL in column, which means aggregate and NULL in column, which means `GROUPINGID` function is the solution to that. This function returns a bitvector corresponding to whether each column is present or not. For each column, a value of "1" is produced for a row in the result set if that column has been aggregated in that row, otherwise the value is "0". This can be used to differentiate when there are nulls in the data. For more details, please refer to Hive's docs . Also, there's indicates whether an expression in a `GROUP BY` clause is aggregated or not for a given row. The value 0 represents a column that is part of the grouping set, while the value 1 represents a column that is not part of the grouping set. `ROLLUP` is a shorthand notation for specifying a common type of grouping set. It represents the given list of expressions and all prefixes of the list, including the empty list. For example: ```sql GROUP BY a, b, c WITH ROLLUP ``` is equivalent to ```sql GROUP BY a, b, c GROUPING SETS ( (a, b, c), (a, b), (a), ( )). ``` `CUBE` is a shorthand notation for specifying a common type of grouping set. It represents the given list and all of its possible subsets - the power set. For example: ```sql GROUP BY a, b, c WITH CUBE ``` is equivalent to ```sql GROUP BY a, b, c GROUPING SETS ( (a, b, c), (a, b), (b, c), (a, c), (a), (b), (c), ( )) ``` ```sql -- use group by expression SELECT abs(x), sum(y) FROM t GROUP BY abs(x); -- use group by column SELECT x, sum(y) FROM t GROUP BY x; -- use group by position SELECT x, sum(y) FROM t GROUP BY 1; -- group by first column in the table; -- use grouping sets SELECT x, SUM(y) FROM t GROUP BY x GROUPING SETS ( x, ( ) ); -- use rollup SELECT x, SUM(y) FROM t GROUP BY x WITH ROLLUP; SELECT x, SUM(y) FROM t GROUP BY ROLLUP (x); -- use cube SELECT x, SUM(y) FROM t GROUP BY x WITH CUBE; SELECT x, SUM(y) FROM t GROUP BY CUBE (x); ```