spark-instrumented-optimizer/docs/sql-ref-syntax-ddl-create-table-datasource.md
GuoPhilipse 3bdbb5546d [SPARK-31753][SQL][DOCS][FOLLOW-UP] Add missing keywords in the SQL docs
### What changes were proposed in this pull request?
update sql-ref docs, the following key words will be added in this PR.

CLUSTERED BY
SORTED BY
INTO num_buckets BUCKETS

### Why are the changes needed?
let more users know the sql key words usage

### Does this PR introduce _any_ user-facing change?
No
![image](https://user-images.githubusercontent.com/46367746/94428281-0a6b8080-01c3-11eb-9ff3-899f8da602ca.png)
![image](https://user-images.githubusercontent.com/46367746/94428285-0d667100-01c3-11eb-8a54-90e7641d917b.png)
![image](https://user-images.githubusercontent.com/46367746/94428288-0f303480-01c3-11eb-9e1d-023538aa6e2d.png)

### How was this patch tested?
generate html test

Closes #29883 from GuoPhilipse/add-sql-missing-keywords.

Lead-authored-by: GuoPhilipse <46367746+GuoPhilipse@users.noreply.github.com>
Co-authored-by: GuoPhilipse <guofei_ok@126.com>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
2020-10-01 08:15:53 +09:00

141 lines
4.8 KiB
Markdown

---
layout: global
title: CREATE DATASOURCE TABLE
displayTitle: CREATE DATASOURCE TABLE
license: |
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.
---
### Description
The `CREATE TABLE` statement defines a new table using a Data Source.
### Syntax
```sql
CREATE TABLE [ IF NOT EXISTS ] table_identifier
[ ( col_name1 col_type1 [ COMMENT col_comment1 ], ... ) ]
USING data_source
[ OPTIONS ( key1=val1, key2=val2, ... ) ]
[ PARTITIONED BY ( col_name1, col_name2, ... ) ]
[ CLUSTERED BY ( col_name3, col_name4, ... )
[ SORTED BY ( col_name [ ASC | DESC ], ... ) ]
INTO num_buckets BUCKETS ]
[ LOCATION path ]
[ COMMENT table_comment ]
[ TBLPROPERTIES ( key1=val1, key2=val2, ... ) ]
[ AS select_statement ]
```
Note that, the clauses between the USING clause and the AS SELECT clause can come in
as any order. For example, you can write COMMENT table_comment after TBLPROPERTIES.
### Parameters
* **table_identifier**
Specifies a table name, which may be optionally qualified with a database name.
**Syntax:** `[ database_name. ] table_name`
* **USING data_source**
Data Source is the input format used to create the table. Data source can be CSV, TXT, ORC, JDBC, PARQUET, etc.
* **PARTITIONED BY**
Partitions are created on the table, based on the columns specified.
* **CLUSTERED BY**
Partitions created on the table will be bucketed into fixed buckets based on the column specified for bucketing.
**NOTE:** Bucketing is an optimization technique that uses buckets (and bucketing columns) to determine data partitioning and avoid data shuffle.
* **SORTED BY**
Specifies an ordering of bucket columns. Optionally, one can use ASC for an ascending order or DESC for a descending order after any column names in the SORTED BY clause.
If not specified, ASC is assumed by default.
* **INTO num_buckets BUCKETS**
Specifies buckets numbers, which is used in `CLUSTERED BY` clause.
* **LOCATION**
Path to the directory where table data is stored, which could be a path on distributed storage like HDFS, etc.
* **COMMENT**
A string literal to describe the table.
* **TBLPROPERTIES**
A list of key-value pairs that is used to tag the table definition.
* **AS select_statement**
The table is populated using the data from the select statement.
### Data Source Interaction
A Data Source table acts like a pointer to the underlying data source. For example, you can create
a table "foo" in Spark which points to a table "bar" in MySQL using JDBC Data Source. When you
read/write table "foo", you actually read/write table "bar".
In general CREATE TABLE is creating a "pointer", and you need to make sure it points to something
existing. An exception is file source such as parquet, json. If you don't specify the LOCATION,
Spark will create a default table location for you.
For CREATE TABLE AS SELECT, Spark will overwrite the underlying data source with the data of the
input query, to make sure the table gets created contains exactly the same data as the input query.
### Examples
```sql
--Use data source
CREATE TABLE student (id INT, name STRING, age INT) USING CSV;
--Use data from another table
CREATE TABLE student_copy USING CSV
AS SELECT * FROM student;
--Omit the USING clause, which uses the default data source (parquet by default)
CREATE TABLE student (id INT, name STRING, age INT);
--Specify table comment and properties
CREATE TABLE student (id INT, name STRING, age INT) USING CSV
COMMENT 'this is a comment'
TBLPROPERTIES ('foo'='bar');
--Specify table comment and properties with different clauses order
CREATE TABLE student (id INT, name STRING, age INT) USING CSV
TBLPROPERTIES ('foo'='bar')
COMMENT 'this is a comment';
--Create partitioned and bucketed table
CREATE TABLE student (id INT, name STRING, age INT)
USING CSV
PARTITIONED BY (age)
CLUSTERED BY (Id) INTO 4 buckets;
```
### Related Statements
* [CREATE TABLE USING HIVE FORMAT](sql-ref-syntax-ddl-create-table-hiveformat.html)
* [CREATE TABLE LIKE](sql-ref-syntax-ddl-create-table-like.html)