SnowConvert AI - Hive - CREATE TABLE¶

Applies to

Hive SQL
Spark SQL
Databricks SQL

Description¶

Creates a new table in the current database. You define a list of columns, which each hold data of a distinct type. The owner of the table is the issuer of the CREATE TABLE command.

For more information, please refer to CREATE TABLE documentation.

Grammar Syntax ¶

--DATASOURCE TABLE
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 ]

--HIVE FORMAT TABLE
CREATE [ EXTERNAL ] TABLE [ IF NOT EXISTS ] table_identifier
    [ ( col_name1[:] col_type1 [ COMMENT col_comment1 ], ... ) ]
    [ COMMENT table_comment ]
    [ PARTITIONED BY ( col_name2[:] col_type2 [ COMMENT col_comment2 ], ... )
        | ( col_name1, col_name2, ... ) ]
    [ CLUSTERED BY ( col_name1, col_name2, ...)
        [ SORTED BY ( col_name1 [ ASC | DESC ], col_name2 [ ASC | DESC ], ... ) ]
        INTO num_buckets BUCKETS ]
    [ ROW FORMAT row_format ]
    [ STORED AS file_format ]
    [ LOCATION path ]
    [ TBLPROPERTIES ( key1=val1, key2=val2, ... ) ]
    [ AS select_statement ]

--LIKE TABLE
CREATE TABLE [IF NOT EXISTS] table_identifier LIKE source_table_identifier
    USING data_source
    [ ROW FORMAT row_format ]
    [ STORED AS file_format ]
    [ TBLPROPERTIES ( key1=val1, key2=val2, ... ) ]
    [ LOCATION path ]

IF NOT EXISTS ¶

Description¶

Ensures the table is created only if it does not already exist, preventing duplication and errors in your SQL script.

Note

:class: hint This syntax is fully supported in Snowflake.

Applies to¶

Hive
Spark
Databricks

Grammar Syntax¶

IF NOT EXISTS

Sample Source Patterns¶

Input Code:¶

CREATE TABLE IF NOT EXISTS table1 (
    col1 INTEGER
);

Output Code:¶

CREATE TABLE IF NOT EXISTS table1 (
    col1 INTEGER
)
COMMENT = '{ "origin": "sf_sc", "name": "snowconvert", "version": {  "major": 0,  "minor": 0,  "patch": "0" }, "attributes": {  "component": "sybase",  "convertedOn": "03/19/2024" }}';

PARTITION BY¶

Description¶

Partitions are created on the table, based on the columns specified.

This syntax is not needed in Snowflake.

Applies to¶

Hive
Spark
Databricks

Grammar Syntax¶

:force:
PARTITIONED BY ( { partition_column [ column_type ] } [, ...] )

Sample Source Patterns¶

Input Code:¶

:force:
CREATE TABLE orders (
    order_id INT,
    customer_id INT,
    order_date DATE,
    total_amount DECIMAL(10, 2),
    order_status STRING
)
PARTITIONED BY (order_status);

Output Code:¶

:force:
CREATE TABLE orders (
    order_id INT,
    customer_id INT,
    order_date DATE,
    total_amount DECIMAL(10, 2),
    order_status STRING
);

CLUSTERED BY¶

Description¶

Partitions created on the table will be bucketed into fixed buckets based on the column specified for bucketing.

This grammar is partially supported

Applies to¶

Hive
Spark
Databricks

Grammar Syntax¶

:force:
CLUSTERED BY (column_name1 [ASC|DESC], ...)
[SORTED BY (sort_column1 [ASC|DESC], ...)]
INTO num_buckets BUCKETS

The CLUSTERED BY clause, used for performance optimization, will be converted to CLUSTER BY in Snowflake. Performance may vary between the two architectures.
The SORTED BY clause can be removed during migration, as Snowflake automatically handles data sorting within its micro-partitions.
The INTO BUCKETS clause, a SparkSQL/Databrick specific partitioning setting, should be entirely eliminated, as it’s not applicable in Snowflake.

Sample Source Patterns¶

Input Code:¶

:force:
CREATE TABLE table_name (
column1 data_type, column2 data_type, ... ) USING format CLUSTERED BY (bucketing_column1) SORTED BY (sorting_column1 DESC, sorting_column2 ASC) INTO 10 BUCKETS;

Output Code:¶

:force:
CREATE TABLE table_name ( column1 data_type, column2 data_type, ... ) USING format
CLUSTER BY (bucketing_column1);

ROW FORMAT¶

Description¶

Specifies the row format for input and output.

This grammar is not supported in Snowflake

Applies to¶

Hive
Spark
Databricks

Grammar Syntax¶

:force:
ROW FORMAT fow_format

row_format:
   { SERDE serde_class [ WITH SERDEPROPERTIES (serde_key = serde_val [, ...] ) ] |
     { DELIMITED [ FIELDS TERMINATED BY fields_terminated_char [ ESCAPED BY escaped_char ] ]
       [ COLLECTION ITEMS TERMINATED BY collection_items_terminated_char ]
       [ MAP KEYS TERMINATED BY map_key_terminated_char ]
       [ LINES TERMINATED BY row_terminated_char ]
       [ NULL DEFINED AS null_char ] } }

Sample Source Patterns¶

Input Code:¶

:force:
CREATE TABLE parquet_table ( id INT, data STRING )  STORED AS TEXTFILE LOCATION '/mnt/delimited/target' ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' ESCAPED BY '\\' COLLECTION ITEMS TERMINATED BY ';' MAP KEYS TERMINATED BY ':' LINES TERMINATED BY '\n' NULL DEFINED AS 'NULL_VALUE';

Output Code:¶

:force:
CREATE TABLE delimited_like_delta LIKE source_delta_table STORED AS TEXTFILE LOCATION '/mnt/delimited/target'
!!!RESOLVE EWI!!! /*** SSC-EWI-HV0002 - THE ROW FORMAT CLAUSE IS NOT SUPPORTED IN SNOWFLAKE ***/!!! ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' ESCAPED BY '\\' COLLECTION ITEMS TERMINATED BY ';' MAP KEYS TERMINATED BY ':' LINES TERMINATED BY '\n' NULL DEFINED AS 'NULL_VALUE';

STORED AS¶

Description¶

File format for table storage.

This grammar is not supported in Snowflake

Applies to¶

Hive
Spark
Databricks