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### What changes were proposed in this pull request? - Sets up links between related sections. - Add "Related sections" for each section. - Change to the left hand side menu to reflect the current status of the doc. - Other minor cleanups. ### Why are the changes needed? Currently Spark lacks documentation on the supported SQL constructs causing confusion among users who sometimes have to look at the code to understand the usage. This is aimed at addressing this issue. ### Does this PR introduce any user-facing change? Yes. ### How was this patch tested? Tested using jykyll build --serve Closes #27371 from dilipbiswal/select_finalization. Authored-by: Dilip Biswal <dkbiswal@gmail.com> Signed-off-by: Sean Owen <srowen@gmail.com>
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| layout | title | displayTitle | license |
|---|---|---|---|
| global | DISTRIBUTE BY Clause | DISTRIBUTE BY Clause | 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 DISTRIBUTE BY clause is used to repartition the data based
on the input expressions. Unlike the CLUSTER BY
clause, this does not sort the data within each partition.
Syntax
{% highlight sql %} DISTRIBUTE BY { expression [ , ... ] } {% endhighlight %}
Parameters
expression- Specifies combination of one or more values, operators and SQL functions that results in a value.
Examples
{% highlight sql %} CREATE TABLE person (name STRING, age INT); INSERT INTO person VALUES ('Zen Hui', 25), ('Anil B', 18), ('Shone S', 16), ('Mike A', 25), ('John A', 18), ('Jack N', 16);
-- Reduce the number of shuffle partitions to 2 to illustrate the behavior of DISTRIBUTE BY.
-- It's easier to see the clustering and sorting behavior with less number of partitions.
SET spark.sql.shuffle.partitions = 2;
-- Select the rows with no ordering. Please note that without any sort directive, the result
-- of the query is not deterministic. It's included here to just contrast it with the
-- behavior of DISTRIBUTE BY. The query below produces rows where age columns are not
-- clustered together.
SELECT age, name FROM person;
+---+-------+ |age|name | +---+-------+ |16 |Shone S| |25 |Zen Hui| |16 |Jack N | |25 |Mike A | |18 |John A | |18 |Anil B | +---+-------+
-- Produces rows clustered by age. Persons with same age are clustered together.
-- Unlike CLUSTER BY clause, the rows are not sorted within a partition.
SELECT age, name FROM person DISTRIBUTE BY age;
+---+-------+ |age|name | +---+-------+ |25 |Zen Hui| |25 |Mike A | |18 |John A | |18 |Anil B | |16 |Shone S| |16 |Jack N | +---+-------+ {% endhighlight %}