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Create Table

CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [db_name.]table_name    -- (Note: TEMPORARY available in Hive 0.14.0 and later)
  [(col_name data_type [COMMENT col_comment], ...)]
  [COMMENT table_comment]
  [PARTITIONED BY (col_name data_type [COMMENT col_comment], ...)]
  [CLUSTERED BY (col_name, col_name, ...) [SORTED BY (col_name [ASC|DESC], ...)] INTO num_buckets BUCKETS]
  [SKEWED BY (col_name, col_name, ...)                  -- (Note: Available in Hive 0.10.0 and later)]
     ON ((col_value, col_value, ...), (col_value, col_value, ...), ...)
     [STORED AS DIRECTORIES]
  [
   [ROW FORMAT row_format] 
   [STORED AS file_format]
     | STORED BY 'storage.handler.class.name' [WITH SERDEPROPERTIES (...)]  -- (Note: Available in Hive 0.6.0 and later)
  ]
  [LOCATION hdfs_path]
  [TBLPROPERTIES (property_name=property_value, ...)]   -- (Note: Available in Hive 0.6.0 and later)
  [AS select_statement];   -- (Note: Available in Hive 0.5.0 and later; not supported for external tables)

CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [db_name.]table_name
  LIKE existing_table_or_view_name
  [LOCATION hdfs_path];

data_type
  : primitive_type
  | array_type
  | map_type
  | struct_type
  | union_type  -- (Note: Available in Hive 0.7.0 and later)

primitive_type
  : TINYINT
  | SMALLINT
  | INT
  | BIGINT
  | BOOLEAN
  | FLOAT
  | DOUBLE
  | DOUBLE PRECISION -- (Note: Available in Hive 2.2.0 and later)
  | STRING
  | BINARY      -- (Note: Available in Hive 0.8.0 and later)
  | TIMESTAMP   -- (Note: Available in Hive 0.8.0 and later)
  | DECIMAL     -- (Note: Available in Hive 0.11.0 and later)
  | DECIMAL(precision, scale)  -- (Note: Available in Hive 0.13.0 and later)
  | DATE        -- (Note: Available in Hive 0.12.0 and later)
  | VARCHAR     -- (Note: Available in Hive 0.12.0 and later)
  | CHAR        -- (Note: Available in Hive 0.13.0 and later)

array_type
  : ARRAY < data_type >

map_type
  : MAP < primitive_type, data_type >

struct_type
  : STRUCT < col_name : data_type [COMMENT col_comment], ...>

union_type
   : UNIONTYPE < data_type, data_type, ... >  -- (Note: Available in Hive 0.7.0 and later)

row_format
  : DELIMITED [FIELDS TERMINATED BY char [ESCAPED BY char]] [COLLECTION ITEMS TERMINATED BY char]
        [MAP KEYS TERMINATED BY char] [LINES TERMINATED BY char]
        [NULL DEFINED AS char]   -- (Note: Available in Hive 0.13 and later)
  | SERDE serde_name [WITH SERDEPROPERTIES (property_name=property_value, property_name=property_value, ...)]

file_format:
  : SEQUENCEFILE
  | TEXTFILE    -- (Default, depending on hive.default.fileformat configuration)
  | RCFILE      -- (Note: Available in Hive 0.6.0 and later)
  | ORC         -- (Note: Available in Hive 0.11.0 and later)
  | PARQUET     -- (Note: Available in Hive 0.13.0 and later)
  | AVRO        -- (Note: Available in Hive 0.14.0 and later)
  | INPUTFORMAT input_format_classname OUTPUTFORMAT output_format_classname

CREATE TABLE creates a table with the given name. An error is thrown if a table or view with the same name already exists. You can use IF NOT EXISTS to skip the error.

• Table names and column names are case insensitive but SerDe and property names are case sensitive.
  • In Hive 0.12 and earlier, only alphanumeric and underscore characters are allowed in table and column names.
  • In Hive 0.13 and later, column names can contain any Unicode character (see HIVE-6013). Any column name that is specified within backticks (`) is treated literally. Within a backtick string, use double backticks (``) to represent a backtick character. Backtick quotation also enables the use of reserved keywords for table and column identifiers.
  • To revert to pre-0.13.0 behavior and restrict column names to alphanumeric and underscore characters, set the configuration property hive.support.quoted.identifiers to none. In this configuration, backticked names are interpreted as regular expressions. For details, see Supporting Quoted Identifiers in Column Names.
• Table and column comments are string literals (single-quoted).

• Anchor
  listTableProperties listTableProperties

  The TBLPROPERTIES clause allows you to tag the table definition with your own metadata key/value pairs. Some predefined table properties also exist, such as last_modified_user and last_modified_time which are automatically added and managed by Hive. Other predefined table properties include:
  • TBLPROPERTIES ("comment"="table_comment")
  • TBLPROPERTIES ("hbase.table.name"="table_name") – see HBase Integration.
  • TBLPROPERTIES ("immutable"="true") or ("immutable"="false") in release 0.13.0+ (HIVE-6406) – see Inserting Data into Hive Tables from Queries.
  • TBLPROPERTIES ("orc.compress"="ZLIB") or ("orc.compress"="SNAPPY") or ("orc.compress"="NONE") and other ORC properties – see ORC Files.
  • TBLPROPERTIES ("transactional"="true") or ("transactional"="false") in release 0.14.0+, the default is "false" – see Hive Transactions.
  • TBLPROPERTIES ("NO_AUTO_COMPACTION"="true") or ("NO_AUTO_COMPACTION"="false"), the default is "false" – see Hive Transactions.
  • TBLPROPERTIES ("compactor.mapreduce.map.memory.mb"="mapper_memory") – see Hive Transactions.
  • TBLPROPERTIES ("compactorthreshold.hive.compactor.delta.num.threshold"="threshold_num") – see Hive Transactions.
  • TBLPROPERTIES ("compactorthreshold.hive.compactor.delta.pct.threshold"="threshold_pct") – see Hive Transactions.
  • TBLPROPERTIES ("auto.purge"="true") or ("auto.purge"="false") in release 1.2.0+ (HIVE-9118) – see Drop Table and Drop Partitions.
  • TBLPROPERTIES ("EXTERNAL"="TRUE") in release 0.6.0+ (HIVE-1329) – Change a managed table to an external table and vice versa for "FALSE".
• To specify a database for the table, either issue the USE database_name statement prior to the CREATE TABLE statement (in Hive 0.6 and later) or qualify the table name with a database name ("database_name.table.name" in Hive 0.7 and later). The keyword "default" can be used for the default database.

See Alter Table below for more information about table comments, table properties, and SerDe properties.

See Type System and Hive Data Types for details about the primitive and complex data types.

Row Format, Storage Format, and SerDe

You can create tables with a custom SerDe or using a native SerDe. A native SerDe is used if ROW FORMAT is not specified or ROW FORMAT DELIMITED is specified. You can use the DELIMITED clause to read delimited files, and you can enable escaping for the delimiter characters by using the 'ESCAPED BY' clause (such as ESCAPED BY '\') – escaping is needed if you want to work with data that can contain these delimiter characters. A custom NULL format can also be specified using the 'NULL DEFINED AS' clause (default is '\N'). Use the SERDE clause to create a table with a custom SerDe. For more information on SerDes see:

• Hive SerDe
• SerDe
• HCatalog Storage Formats

You must specify a list of columns for tables that use a native SerDe. Refer to the Types part of the User Guide for the allowable column types. A list of columns for tables that use a custom SerDe may be specified but Hive will query the SerDe to determine the actual list of columns for this table.

Use STORED AS TEXTFILE if the data needs to be stored as plain text files. TEXTFILE is the default file format, unless the configuration parameter hive.default.fileformat has a different setting.

Use STORED AS SEQUENCEFILE if the data needs to be compressed. Please read more about CompressedStorage if you are planning to keep data compressed in your Hive tables.

Use STORED AS ORC if the data needs to be stored in ORC file format.

Use ROW FORMAT SERDE for the RegEx SerDe, as shown in the example Apache Weblog Data in Getting Started.

Use INPUTFORMAT and OUTPUTFORMAT in the file_format to specify the name of a corresponding InputFormat and OutputFormat class as a string literal, for example, 'org.apache.hadoop.hive.contrib.fileformat.base64.Base64TextInputFormat'. For LZO compression, the values to use are 'INPUTFORMAT "com.hadoop.mapred.DeprecatedLzoTextInputFormat" OUTPUTFORMAT "org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat"' (see LZO Compression).

Use STORED AS PARQUET (without ROW FORMAT SERDE) for the Parquet columnar storage format in Hive 0.13.0 and later; or use ROW FORMAT SERDE ... STORED AS INPUTFORMAT ... OUTPUTFORMAT ... in Hive 0.10, 0.11, or 0.12.

Use STORED AS AVRO for Avro files in Hive 0.14.0 and later (see Avro SerDe).

Use STORED BY to create a non-native table, for example in HBase. See StorageHandlers for more information on this option.

To change a table's SerDe or SERDEPROPERTIES, use the ALTER TABLE statement as described below in Add SerDe Properties.

Partitioned Tables

Partitioned tables can be created using the PARTITIONED BY clause. A table can have one or more partition columns and a separate data directory is created for each distinct value combination in the partition columns. Further, tables or partitions can be bucketed using CLUSTERED BY columns, and data can be sorted within that bucket via SORT BY columns. This can improve performance on certain kinds of queries.

If, when creating a partitioned table, you get this error: "FAILED: Error in semantic analysis: Column repeated in partitioning columns," it means you are trying to include the partitioned column in the data of the table itself. You probably really do have the column defined. However, the partition you create makes a pseudocolumn on which you can query, so you must rename your table column to something else (that users should not query on!).

For example, suppose your original unpartitioned table had three columns: id, date, and name.

id     int,
date   date,
name   varchar

Now you want to partition on date. Your Hive definition could use "dtDontQuery" as a column name so that "date" can be used for partitioning (and querying).

create table table_name (
  id                int,
  dtDontQuery       string,
  name              string
)
partitioned by (date string)

Now your users will still query on "where date = '...'" but the second column dtDontQuery will hold the original values.

Here's an example statement to create a partitioned table:

CREATE TABLE page_view(viewTime INT, userid BIGINT,
     page_url STRING, referrer_url STRING,
     ip STRING COMMENT 'IP Address of the User')
 COMMENT 'This is the page view table'
 PARTITIONED BY(dt STRING, country STRING)
 STORED AS SEQUENCEFILE;

The statement above creates the page_view table with viewTime, userid, page_url, referrer_url, and ip columns (including comments). The table is also partitioned and data is stored in sequence files. The data format in the files is assumed to be field-delimited by ctrl-A and row-delimited by newline.

CREATE TABLE page_view(viewTime INT, userid BIGINT,
     page_url STRING, referrer_url STRING,
     ip STRING COMMENT 'IP Address of the User')
 COMMENT 'This is the page view table'
 PARTITIONED BY(dt STRING, country STRING)
 ROW FORMAT DELIMITED
   FIELDS TERMINATED BY '\001'
STORED AS SEQUENCEFILE;

The above statement lets you create the same table as the previous table.

In the previous examples the data is stored in <hive.metastore.warehouse.dir>/page_view. Specify a value for the key hive.metastore.warehouse.dir in the Hive config file hive-site.xml.

External Tables

The EXTERNAL keyword lets you create a table and provide a LOCATION so that Hive does not use a default location for this table. This comes in handy if you already have data generated. When dropping an EXTERNAL table, data in the table is NOT deleted from the file system.

An EXTERNAL table points to any HDFS location for its storage, rather than being stored in a folder specified by the configuration property hive.metastore.warehouse.dir.

CREATE EXTERNAL TABLE page_view(viewTime INT, userid BIGINT,
     page_url STRING, referrer_url STRING,
     ip STRING COMMENT 'IP Address of the User',
     country STRING COMMENT 'country of origination')
 COMMENT 'This is the staging page view table'
 ROW FORMAT DELIMITED FIELDS TERMINATED BY '\054'
 STORED AS TEXTFILE
 LOCATION '<hdfs_location>';

You can use the above statement to create a page_view table which points to any HDFS location for its storage. But you still have to make sure that the data is delimited as specified in the CREATE statement above.

For another example of creating an external table, see Loading Data in the Tutorial.

Create Table As Select (CTAS)

Tables can also be created and populated by the results of a query in one create-table-as-select (CTAS) statement. The table created by CTAS is atomic, meaning that the table is not seen by other users until all the query results are populated. So other users will either see the table with the complete results of the query or will not see the table at all.

There are two parts in CTAS, the SELECT part can be any SELECT statement supported by HiveQL. The CREATE part of the CTAS takes the resulting schema from the SELECT part and creates the target table with other table properties such as the SerDe and storage format.

CTAS has these restrictions:

• The target table cannot be a partitioned table.
• The target table cannot be an external table.
• The target table cannot be a list bucketing table.

CREATE TABLE new_key_value_store
   ROW FORMAT SERDE "org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe"
   STORED AS RCFile
   AS
SELECT (key % 1024) new_key, concat(key, value) key_value_pair
FROM key_value_store
SORT BY new_key, key_value_pair;

The above CTAS statement creates the target table new_key_value_store with the schema (new_key DOUBLE, key_value_pair STRING) derived from the results of the SELECT statement. If the SELECT statement does not specify column aliases, the column names will be automatically assigned to _col0, _col1, and _col2 etc. In addition, the new target table is created using a specific SerDe and a storage format independent of the source tables in the SELECT statement.

Starting with Hive 0.13.0, the SELECT statement can include one or more common table expressions (CTEs), as shown in the SELECT syntax. For an example, see Common Table Expression.

Being able to select data from one table to another is one of the most powerful features of Hive. Hive handles the conversion of the data from the source format to the destination format as the query is being executed.

Create Table Like

The LIKE form of CREATE TABLE allows you to copy an existing table definition exactly (without copying its data). In contrast to CTAS, the statement below creates a new empty_key_value_store table whose definition exactly matches the existing key_value_store in all particulars other than table name. The new table contains no rows.

CREATE TABLE empty_key_value_store
LIKE key_value_store;

Before Hive 0.8.0, CREATE TABLE LIKE view_name would make a copy of the view. In Hive 0.8.0 and later releases, CREATE TABLE LIKE view_name creates a table by adopting the schema of view_name (fields and partition columns) using defaults for SerDe and file formats.

Bucketed Sorted Tables

CREATE TABLE page_view(viewTime INT, userid BIGINT,
     page_url STRING, referrer_url STRING,
     ip STRING COMMENT 'IP Address of the User')
 COMMENT 'This is the page view table'
 PARTITIONED BY(dt STRING, country STRING)
 CLUSTERED BY(userid) SORTED BY(viewTime) INTO 32 BUCKETS
 ROW FORMAT DELIMITED
   FIELDS TERMINATED BY '\001'
   COLLECTION ITEMS TERMINATED BY '\002'
   MAP KEYS TERMINATED BY '\003'
 STORED AS SEQUENCEFILE;

In the example above, the page_view table is bucketed (clustered by) userid and within each bucket the data is sorted in increasing order of viewTime. Such an organization allows the user to do efficient sampling on the clustered column - in this case userid. The sorting property allows internal operators to take advantage of the better-known data structure while evaluating queries, also increasing efficiency. MAP KEYS and COLLECTION ITEMS keywords can be used if any of the columns are lists or maps.

The CLUSTERED BY and SORTED BY creation commands do not affect how data is inserted into a table – only how it is read. This means that users must be careful to insert data correctly by specifying the number of reducers to be equal to the number of buckets, and using CLUSTER BY and SORT BY commands in their query.

There is also an example of creating and populating bucketed tables.

Skewed Tables

This feature can be used to improve performance for tables where one or more columns have skewed values. By specifying the values that appear very often (heavy skew) Hive will split those out into separate files (or directories in case of list bucketing) automatically and take this fact into account during queries so that it can skip or include the whole file (or directory in case of list bucketing) if possible.

This can be specified on a per-table level during table creation.

The following example shows one column with three skewed values, optionally with the STORED AS DIRECTORIES clause which specifies list bucketing.

CREATE TABLE list_bucket_single (key STRING, value STRING)
  SKEWED BY (key) ON (1,5,6) [STORED AS DIRECTORIES];

And here is an example of a table with two skewed columns.

CREATE TABLE list_bucket_multiple (col1 STRING, col2 int, col3 STRING)
  SKEWED BY (col1, col2) ON (('s1',1), ('s3',3), ('s13',13), ('s78',78)) [STORED AS DIRECTORIES];

For corresponding ALTER TABLE statements, see Alter Table Skewed or Stored as Directories below.

Temporary Tables

A table that has been created as a temporary table will only be visible to the current session. Data will be stored in the user's scratch directory, and deleted at the end of the session.

If a temporary table is created with a database/table name of a permanent table which already exists in the database, then within that session any references to that table will resolve to the temporary table, rather than to the permanent table. The user will not be able to access the original table within that session without either dropping the temporary table, or renaming it to a non-conflicting name.

Temporary tables have the following limitations:

• Partition columns are not supported.
• No support for creation of indexes.

Starting in Hive 1.1.0 the storage policy for temporary tables can be set to memory, ssd, or default with the hive.exec.temporary.table.storage configuration parameter (see HDFS Storage Types and Storage Policies).

Drop Table

DROP TABLE [IF EXISTS] table_name [PURGE];     -- (Note: PURGE available in Hive 0.14.0 and later)

DROP TABLE removes metadata and data for this table. The data is actually moved to the .Trash/Current directory if Trash is configured (and PURGE is not specified). The metadata is completely lost.

When dropping an EXTERNAL table, data in the table will NOT be deleted from the file system.

When dropping a table referenced by views, no warning is given (the views are left dangling as invalid and must be dropped or recreated by the user).

Otherwise, the table information is removed from the metastore and the raw data is removed as if by 'hadoop dfs -rm'. In many cases, this results in the table data being moved into the user's .Trash folder in their home directory; users who mistakenly DROP TABLEs may thus be able to recover their lost data by recreating a table with the same schema, recreating any necessary partitions, and then moving the data back into place manually using Hadoop. This solution is subject to change over time or across installations as it relies on the underlying implementation; users are strongly encouraged not to drop tables capriciously.

If PURGE is specified, the table data does not go to the .Trash/Current directory and so cannot be retrieved in the event of a mistaken DROP. The purge option can also be specified with the table property auto.purge (see Create Table above).

In Hive 0.7.0 or later, DROP returns an error if the table doesn't exist, unless IF EXISTS is specified or the configuration variable hive.exec.drop.ignorenonexistent is set to true.

See the Alter Partition section below for how to drop partitions.

Truncate Table

TRUNCATE TABLE table_name [PARTITION partition_spec];

partition_spec:
  : (partition_column = partition_col_value, partition_column = partition_col_value, ...)

Removes all rows from a table or partition(s). The rows will be trashed if the filesystem Trash is enabled, otherwise they are deleted (as of Hive 2.2.0 with HIVE-14626). Currently the target table should be native/managed table or an exception will be thrown. User can specify partial partition_spec for truncating multiple partitions at once and omitting partition_spec will truncate all partitions in the table.