CREATE TABLE¶

Syntax¶

CREATE [ OR REPLACE ]
    [ { [ { LOCAL | GLOBAL } ] TEMP | TEMPORARY | VOLATILE | TRANSIENT } ]
  TABLE [ IF NOT EXISTS ] <table_name> (
    -- Column definition
    <col_name> <col_type>
      [ inlineConstraint ]
      [ NOT NULL ]
      [ COLLATE '<collation_specification>' ]
      [
        {
          DEFAULT <expr>
          | { AUTOINCREMENT | IDENTITY }
            [
              {
                ( <start_num> , <step_num> )
                | START <num> INCREMENT <num>
              }
            ]
            [ { ORDER | NOORDER } ]
        }
      ]
      [ [ WITH ] MASKING POLICY <policy_name> [ USING ( <col_name> , <cond_col1> , ... ) ] ]
      [ [ WITH ] TAG ( <tag_name> = '<tag_value>' [ , <tag_name> = '<tag_value>' , ... ] ) ]
      [ COMMENT '<string_literal>' ]

    -- Additional column definitions
    [ , <col_name> <col_type> [ ... ] ]

    -- Out-of-line constraints
    [ , outoflineConstraint [ ... ] ]
  )
  [ CLUSTER BY ( <expr> [ , <expr> , ... ] ) ]
  [ ENABLE_SCHEMA_EVOLUTION = { TRUE | FALSE } ]
  [ STAGE_FILE_FORMAT = (
     { FORMAT_NAME = '<file_format_name>'
       | TYPE = { CSV | JSON | AVRO | ORC | PARQUET | XML } [ formatTypeOptions ]
     } ) ]
  [ STAGE_COPY_OPTIONS = ( copyOptions ) ]
  [ DATA_RETENTION_TIME_IN_DAYS = <integer> ]
  [ MAX_DATA_EXTENSION_TIME_IN_DAYS = <integer> ]
  [ CHANGE_TRACKING = { TRUE | FALSE } ]
  [ DEFAULT_DDL_COLLATION = '<collation_specification>' ]
  [ COPY GRANTS ]
  [ COMMENT = '<string_literal>' ]
  [ [ WITH ] ROW ACCESS POLICY <policy_name> ON ( <col_name> [ , <col_name> ... ] ) ]
  [ [ WITH ] TAG ( <tag_name> = '<tag_value>' [ , <tag_name> = '<tag_value>' , ... ] ) ]

Where:

inlineConstraint ::=
  [ CONSTRAINT <constraint_name> ]
  { UNIQUE
    | PRIMARY KEY
    | [ FOREIGN KEY ] REFERENCES <ref_table_name> [ ( <ref_col_name> ) ]
  }
  [ <constraint_properties> ]

Copy

For additional inline constraint details, see CREATE | ALTER TABLE … CONSTRAINT.

outoflineConstraint ::=
  [ CONSTRAINT <constraint_name> ]
  { UNIQUE [ ( <col_name> [ , <col_name> , ... ] ) ]
    | PRIMARY KEY [ ( <col_name> [ , <col_name> , ... ] ) ]
    | [ FOREIGN KEY ] [ ( <col_name> [ , <col_name> , ... ] ) ]
      REFERENCES <ref_table_name> [ ( <ref_col_name> [ , <ref_col_name> , ... ] ) ]
  }
  [ <constraint_properties> ]

Copy

For additional out-of-line constraint details, see CREATE | ALTER TABLE … CONSTRAINT.

formatTypeOptions ::=
-- If TYPE = CSV
     COMPRESSION = AUTO | GZIP | BZ2 | BROTLI | ZSTD | DEFLATE | RAW_DEFLATE | NONE
     RECORD_DELIMITER = '<character>' | NONE
     FIELD_DELIMITER = '<character>' | NONE
     FILE_EXTENSION = '<string>'
     PARSE_HEADER = TRUE | FALSE
     SKIP_HEADER = <integer>
     SKIP_BLANK_LINES = TRUE | FALSE
     DATE_FORMAT = '<string>' | AUTO
     TIME_FORMAT = '<string>' | AUTO
     TIMESTAMP_FORMAT = '<string>' | AUTO
     BINARY_FORMAT = HEX | BASE64 | UTF8
     ESCAPE = '<character>' | NONE
     ESCAPE_UNENCLOSED_FIELD = '<character>' | NONE
     TRIM_SPACE = TRUE | FALSE
     FIELD_OPTIONALLY_ENCLOSED_BY = '<character>' | NONE
     NULL_IF = ( '<string>' [ , '<string>' ... ] )
     ERROR_ON_COLUMN_COUNT_MISMATCH = TRUE | FALSE
     REPLACE_INVALID_CHARACTERS = TRUE | FALSE
     EMPTY_FIELD_AS_NULL = TRUE | FALSE
     SKIP_BYTE_ORDER_MARK = TRUE | FALSE
     ENCODING = '<string>' | UTF8
-- If TYPE = JSON
     COMPRESSION = AUTO | GZIP | BZ2 | BROTLI | ZSTD | DEFLATE | RAW_DEFLATE | NONE
     DATE_FORMAT = '<string>' | AUTO
     TIME_FORMAT = '<string>' | AUTO
     TIMESTAMP_FORMAT = '<string>' | AUTO
     BINARY_FORMAT = HEX | BASE64 | UTF8
     TRIM_SPACE = TRUE | FALSE
     NULL_IF = ( '<string>' [ , '<string>' ... ] )
     FILE_EXTENSION = '<string>'
     ENABLE_OCTAL = TRUE | FALSE
     ALLOW_DUPLICATE = TRUE | FALSE
     STRIP_OUTER_ARRAY = TRUE | FALSE
     STRIP_NULL_VALUES = TRUE | FALSE
     REPLACE_INVALID_CHARACTERS = TRUE | FALSE
     IGNORE_UTF8_ERRORS = TRUE | FALSE
     SKIP_BYTE_ORDER_MARK = TRUE | FALSE
-- If TYPE = AVRO
     COMPRESSION = AUTO | GZIP | BROTLI | ZSTD | DEFLATE | RAW_DEFLATE | NONE
     TRIM_SPACE = TRUE | FALSE
     REPLACE_INVALID_CHARACTERS = TRUE | FALSE
     NULL_IF = ( '<string>' [ , '<string>' ... ] )
-- If TYPE = ORC
     TRIM_SPACE = TRUE | FALSE
     REPLACE_INVALID_CHARACTERS = TRUE | FALSE
     NULL_IF = ( '<string>' [ , '<string>' ... ] )
-- If TYPE = PARQUET
     COMPRESSION = AUTO | LZO | SNAPPY | NONE
     SNAPPY_COMPRESSION = TRUE | FALSE
     BINARY_AS_TEXT = TRUE | FALSE
     USE_LOGICAL_TYPE = TRUE | FALSE
     TRIM_SPACE = TRUE | FALSE
     REPLACE_INVALID_CHARACTERS = TRUE | FALSE
     NULL_IF = ( '<string>' [ , '<string>' ... ] )
-- If TYPE = XML
     COMPRESSION = AUTO | GZIP | BZ2 | BROTLI | ZSTD | DEFLATE | RAW_DEFLATE | NONE
     IGNORE_UTF8_ERRORS = TRUE | FALSE
     PRESERVE_SPACE = TRUE | FALSE
     STRIP_OUTER_ELEMENT = TRUE | FALSE
     DISABLE_SNOWFLAKE_DATA = TRUE | FALSE
     DISABLE_AUTO_CONVERT = TRUE | FALSE
     REPLACE_INVALID_CHARACTERS = TRUE | FALSE
     SKIP_BYTE_ORDER_MARK = TRUE | FALSE

Copy

copyOptions ::=
     ON_ERROR = { CONTINUE | SKIP_FILE | SKIP_FILE_<num> | 'SKIP_FILE_<num>%' | ABORT_STATEMENT }
     SIZE_LIMIT = <num>
     PURGE = TRUE | FALSE
     RETURN_FAILED_ONLY = TRUE | FALSE
     MATCH_BY_COLUMN_NAME = CASE_SENSITIVE | CASE_INSENSITIVE | NONE
     ENFORCE_LENGTH = TRUE | FALSE
     TRUNCATECOLUMNS = TRUE | FALSE
     FORCE = TRUE | FALSE

Copy

Variant Syntax¶

Required Parameters¶

name

Specifies the identifier (i.e. name) for the table; must be unique for the schema in which the table is created.

In addition, the identifier must start with an alphabetic character and cannot contain spaces or special characters unless the entire identifier string is enclosed in double quotes (e.g. "My object"). Identifiers enclosed in double quotes are also case-sensitive.

For more details, see Identifier Requirements.

col_name

Specifies the column identifier (i.e. name). All the requirements for table identifiers also apply to column identifiers.

For more details, see Identifier Requirements and Reserved & Limited Keywords.

Note

In addition to the standard reserved keywords, the following keywords cannot be used as column identifiers because they are reserved for ANSI-standard context functions:

• CURRENT_DATE

• CURRENT_ROLE

• CURRENT_TIME

• CURRENT_TIMESTAMP

• CURRENT_USER

For the list of reserved keywords, see Reserved & Limited Keywords.

col_type

Specifies the data type for the column.

For details about the data types that can be specified for table columns, see Data Types.

query

Required if using USING TEMPLATE

Subquery that calls the INFER_SCHEMA function and formats the output as an array.

Alternatively, USING TEMPLATE accepts the INFER_SCHEMA output as a string literal or variable.

Optional Parameters¶

{ [ { LOCAL | GLOBAL } ] TEMP | TEMPORARY | VOLATILE | TRANSIENT }

Specifies that the table persists only for the duration of the session that you created it in. A temporary table and all its contents are dropped at the end of the session.

The synonyms and abbreviations for TEMPORARY (e.g. GLOBAL TEMPORARY) are provided for compatibility with other databases (e.g. to prevent errors when migrating CREATE TABLE statements). Tables created with any of these keywords appear and behave identically to a table created with the TEMPORARY keyword.

Default: No value. If a table is not declared as TEMPORARY or TRANSIENT, the table is permanent.

If you want to avoid unexpected conflicts, avoid naming temporary tables after tables that already exist in the schema.

If you created a temporary table with the same name as another table in the schema, all queries and operations used on the table only affect the temporary table in the session, until you drop the temporary table. If you drop the table, you drop the temporary table, and not the table that already exists in the schema.

For information about temporary or transient tables, and how they can affect storage and cost, refer to the following resources:

• Working with Temporary and Transient Tables

• Storage Costs for Time Travel and Fail-safe

TRANSIENT

Specifies that the table is transient.

Like a permanent table, a transient table exists until explicitly dropped and is visible to any user with the appropriate privileges. However, transient tables have a lower level of data protection than permanent tables, meaning that data in a transient table might be lost in the event of a system failure. As such, transient tables should only be used for data that can be recreated externally to Snowflake.

Default: No value. If a table is not declared as TRANSIENT or TEMPORARY, the table is permanent.

Note

Transient tables have some storage considerations.

For more information about these and other considerations when deciding whether to create temporary or transient tables, see Working with Temporary and Transient Tables and Storage Costs for Time Travel and Fail-safe.

CONSTRAINT ...

Defines an inline or out-of-line constraint for the specified column(s) in the table.

For syntax details, see CREATE | ALTER TABLE … CONSTRAINT. For more information about constraints, see Constraints.

COLLATE 'collation_specification'

Specifies the collation to use for column operations such as string comparison. This option applies only to text columns (VARCHAR, STRING, TEXT, etc.). For more details, see Collation Specifications.

DEFAULT ... or . AUTOINCREMENT ...

Specifies whether a default value is automatically inserted in the column if a value is not explicitly specified via an INSERT or CREATE TABLE AS SELECT statement:

DEFAULT expr

Column default value is defined by the specified expression which can be any of the following:

• Constant value.

• Sequence reference (seq_name.NEXTVAL).

• Simple expression that returns a scalar value.

  The simple expression can include a SQL UDF (user-defined function) if the UDF is not a secure UDF.

  Note

  If a default expression refers to a SQL UDF, then the function is replaced by its definition at table creation time. If the user-defined function is redefined in the future, this does not update the column’s default expression.

  The simple expression cannot contain references to:

  • Subqueries.

  • Aggregates.

  • Window functions.

  • Secure UDFs.

  • UDFs written in languages other than SQL (e.g. Java, JavaScript).

  • External functions.

{ AUTOINCREMENT | IDENTITY } . [ { ( start_num , step_num ) | START num INCREMENT num } ] . [ { ORDER | NOORDER } ]

When you specify AUTOINCREMENT or IDENTITY, the default value for the column starts with a specified number and each successive value automatically increments by the specified amount.

AUTOINCREMENT and IDENTITY are synonymous and can be used only for columns with numeric data types, such as NUMBER, INT, FLOAT.

Caution

Snowflake uses a sequence to generate the values for an auto-incremented column. Sequences have limitations; see Sequence Semantics.

The default value for both the start value and the step/increment value is 1.

Use ORDER or NOORDER to specify whether or not the values are generated for the sequence in increasing or decreasing order.

• ORDER specifies that the values generated for a sequence or auto-incremented column are in increasing order (or, if the interval is a negative value, in decreasing order).

• NOORDER specifies that the values are not guaranteed to be in any order.

Note

DEFAULT and AUTOINCREMENT are mutually exclusive; only one can be specified for a column.

MASKING POLICY = policy_name

Specifies the masking policy to set on a column.

COMMENT 'string_literal'

Specifies a comment for the column.

(Note that comments can be specified at the column level or the table level. The syntax for each is slightly different.)

USING ( col_name , cond_col_1 ... )

Specifies the arguments to pass into the conditional masking policy SQL expression.

The first column in the list specifies the column for the policy conditions to mask or tokenize the data and must match the column to which the masking policy is set.

The additional columns specify the columns to evaluate to determine whether to mask or tokenize the data in each row of the query result when a query is made on the first column.

If the USING clause is omitted, Snowflake treats the conditional masking policy as a normal masking policy.

CLUSTER BY ( expr [ , expr , ... ] )

Specifies one or more columns or column expressions in the table as the clustering key. For more details, see Clustering Keys & Clustered Tables.

Default: No value (no clustering key is defined for the table)

Important

Clustering keys are not intended or recommended for all tables; they typically benefit very large (i.e. multi-terabyte) tables.

Before you specify a clustering key for a table, you should understand micro-partitions. For more information, see Understanding Snowflake Table Structures.

ENABLE_SCHEMA_EVOLUTION = { TRUE | FALSE }

Preview Feature — Open

Available to all accounts.

Enables or disables automatic changes to the table schema from data loaded into the table from source files, including:

• Added columns.

  By default, schema evolution is limited to a maximum of 10 added columns per load operation. To request more than 10 added columns per load operation, contact Snowflake Support.

• The NOT NULL constraint can be dropped from any number of columns missing in new data files.

Setting it to TRUE enables automatic table schema evolution. The default FALSE disables automatic table schema evolution.

Note

Loading data from files evolves the table columns when all of the following are true:

• The COPY INTO <table> statement includes the MATCH_BY_COLUMN_NAME option.

• The role used to load the data has the EVOLVE SCHEMA or OWNERSHIP privilege on the table.

Additionally, for schema evolution with CSV, when used with MATCH_BY_COLUMN_NAME and PARSE_HEADER, ERROR_ON_COLUMN_COUNT_MISMATCH must be set to false.

STAGE_FILE_FORMAT = ( FORMAT_NAME = 'file_format_name' ) or . STAGE_FILE_FORMAT = ( TYPE = CSV | JSON | AVRO | ORC | PARQUET | XML [ ... ] )

Specifies the default file format for the table (for data loading and unloading), which can be either:

FORMAT_NAME = file_format_name

Specifies an existing named file format to use for loading/unloading data into the table. The named file format determines the format type (CSV, JSON, etc.), as well as any other format options, for data files. For more details, see CREATE FILE FORMAT.

TYPE = CSV | JSON | AVRO | ORC | PARQUET | XML [ ... ]

Specifies the type of files to load/unload into the table.

If a file format type is specified, additional format-specific options can be specified. For more details, see Format Type Options (in this topic).

Default: TYPE = CSV

Note

FORMAT_NAME and TYPE are mutually exclusive; to avoid unintended behavior, you should only specify one or the other when creating a table.

STAGE_COPY_OPTIONS = ( ... )

Specifies one (or more) options to use when loading data into the table. For more details, see Copy Options (in this topic).

DATA_RETENTION_TIME_IN_DAYS = integer

Specifies the retention period for the table so that Time Travel actions (SELECT, CLONE, UNDROP) can be performed on historical data in the table. For more details, see Understanding & Using Time Travel and Working with Temporary and Transient Tables.

For a detailed description of this object-level parameter, as well as more information about object parameters, see Parameters.

Values:

• Standard Edition: 0 or 1

• Enterprise Edition:

  • 0 to 90 for permanent tables

  • 0 or 1 for temporary and transient tables

Default:

• Standard Edition: 1

• Enterprise Edition (or higher): 1 (unless a different default value was specified at the schema, database, or account level)

Note

A value of 0 effectively disables Time Travel for the table.

MAX_DATA_EXTENSION_TIME_IN_DAYS = integer

Object parameter that specifies the maximum number of days for which Snowflake can extend the data retention period for the table to prevent streams on the table from becoming stale.

For a detailed description of this parameter, see MAX_DATA_EXTENSION_TIME_IN_DAYS.

CHANGE_TRACKING = { TRUE | FALSE }

Specifies whether to enable change tracking on the table.

• TRUE enables change tracking on the table. This setting adds a pair of hidden columns to the source table and begins storing change tracking metadata in the columns. These columns consume a small amount of storage.

  The change tracking metadata can be queried using the CHANGES clause for SELECT statements, or by creating and querying one or more streams on the table.

• FALSE does not enable change tracking on the table.

Default: FALSE

DEFAULT_DDL_COLLATION = 'collation_specification'

Specifies a default collation specification for the columns in the table, including columns added to the table in the future.

For more details about the parameter, see DEFAULT_DDL_COLLATION.

COPY GRANTS

Specifies to retain the access privileges from the original table when a new table is created using any of the following CREATE TABLE variants:

• CREATE OR REPLACE TABLE

• CREATE TABLE … LIKE

• CREATE TABLE … CLONE

The parameter copies all privileges, except OWNERSHIP, from the existing table to the new table. The new table does not inherit any future grants defined for the object type in the schema. By default, the role that executes the CREATE TABLE statement owns the new table.

If the parameter is not included in the CREATE TABLE statement, then the new table does not inherit any explicit access privileges granted on the original table, but does inherit any future grants defined for the object type in the schema.

Note:

• With data sharing:

  • If the existing table was shared to another account, the replacement table is also shared.

  • If the existing table was shared with your account as a data consumer, and access was further granted to other roles in the account (using GRANT IMPORTED PRIVILEGES on the parent database), access is also granted to the replacement table.

• The SHOW GRANTS output for the replacement table lists the grantee for the copied privileges as the role that executed the CREATE TABLE statement, with the current timestamp when the statement was executed.

• The operation to copy grants occurs atomically in the CREATE TABLE command (i.e. within the same transaction).

COMMENT = 'string_literal'

Specifies a comment for the table.

Default: No value

(Note that comments can be specified at the column level or the table level. The syntax for each is slightly different.)

ROW ACCESS POLICY policy_name ON ( col_name [ , col_name ... ] )

Specifies the row access policy to set on a table.

TAG ( tag_name = 'tag_value' [ , tag_name = 'tag_value' , ... ] )

Specifies the tag name and the tag string value.

The tag value is always a string, and the maximum number of characters for the tag value is 256.

For details about specifying tags in a statement, refer to Tag Quotas for Objects & Columns.

Format Type Options (formatTypeOptions)¶

Format type options are used for loading data into and unloading data out of tables.

Depending on the file format type specified (STAGE_FILE_FORMAT = ( TYPE = ... )), you can include one or more of the following format-specific options (separated by blank spaces, commas, or new lines):

Copy Options (copyOptions)¶

Copy options are used for loading data into and unloading data out of tables.

You can specify one or more of the following copy options (separated by blank spaces, commas, or new lines):

STAGE_COPY_OPTIONS = ( ... )

ON_ERROR = CONTINUE | SKIP_FILE | SKIP_FILE_num | 'SKIP_FILE_num%' | ABORT_STATEMENT

Use

Data loading only

Definition

String (constant) that specifies the error handling for the load operation.

Important

Carefully consider the ON_ERROR copy option value. The default value is appropriate in common scenarios, but is not always the best option.

Values

• CONTINUE

  Continue to load the file if errors are found. The COPY statement returns an error message for a maximum of one error found per data file.

  Note that the difference between the ROWS_PARSED and ROWS_LOADED column values represents the number of rows that include detected errors. However, each of these rows could include multiple errors. To view all errors in the data files, use the VALIDATION_MODE parameter or query the VALIDATE function.

• SKIP_FILE

  Skip a file when an error is found.

  Note that the SKIP_FILE action buffers an entire file whether errors are found or not. For this reason, SKIP_FILE is slower than either CONTINUE or ABORT_STATEMENT. Skipping large files due to a small number of errors could result in delays and wasted credits. When loading large numbers of records from files that have no logical delineation (e.g. the files were generated automatically at rough intervals), consider specifying CONTINUE instead.

  Additional patterns:

  SKIP_FILE_num (e.g. SKIP_FILE_10)

  Skip a file when the number of error rows found in the file is equal to or exceeds the specified number.

  'SKIP_FILE_num%' (e.g. 'SKIP_FILE_10%')

  Skip a file when the percentage of error rows found in the file exceeds the specified percentage.

• ABORT_STATEMENT

  Abort the load operation if any error is found in a data file.

  Note that the load operation is not aborted if the data file cannot be found (e.g. because it does not exist or cannot be accessed), except when data files explicitly specified in the FILES parameter cannot be found.

Default

Bulk loading using COPY

ABORT_STATEMENT

Snowpipe

SKIP_FILE

SIZE_LIMIT = num

Use

Data loading only

Definition

Number (> 0) that specifies the maximum size (in bytes) of data to be loaded for a given COPY statement. When the threshold is exceeded, the COPY operation discontinues loading files. This option is commonly used to load a common group of files using multiple COPY statements. For each statement, the data load continues until the specified SIZE_LIMIT is exceeded, before moving on to the next statement.

For example, suppose a set of files in a stage path were each 10 MB in size. If multiple COPY statements set SIZE_LIMIT to 25000000 (25 MB), each would load 3 files. That is, each COPY operation would discontinue after the SIZE_LIMIT threshold was exceeded.

Note that at least one file is loaded regardless of the value specified for SIZE_LIMIT unless there is no file to be loaded.

Default

null (no size limit)

PURGE = TRUE | FALSE

Use

Data loading only

Definition

Boolean that specifies whether to remove the data files from the stage automatically after the data is loaded successfully.

If this option is set to TRUE, note that a best effort is made to remove successfully loaded data files. If the purge operation fails for any reason, no error is returned currently. We recommend that you list staged files periodically (using LIST) and manually remove successfully loaded files, if any exist.

Default

FALSE

RETURN_FAILED_ONLY = TRUE | FALSE

Use

Data loading only

Definition

Boolean that specifies whether to return only files that have failed to load in the statement result.

Default

FALSE

MATCH_BY_COLUMN_NAME = CASE_SENSITIVE | CASE_INSENSITIVE | NONE

Use

Data loading only

Definition

String that specifies whether to load semi-structured data into columns in the target table that match corresponding columns represented in the data.

This copy option is supported for the following data formats:

• JSON

• Avro

• ORC

• Parquet

For a column to match, the following criteria must be true:

• The column represented in the data must have the exact same name as the column in the table. The copy option supports case sensitivity for column names. Column order does not matter.

• The column in the table must have a data type that is compatible with the values in the column represented in the data. For example, string, number, and Boolean values can all be loaded into a variant column.

Values

CASE_SENSITIVE | CASE_INSENSITIVE

Load semi-structured data into columns in the target table that match corresponding columns represented in the data. Column names are either case-sensitive (CASE_SENSITIVE) or case-insensitive (CASE_INSENSITIVE).

The COPY operation verifies that at least one column in the target table matches a column represented in the data files. If a match is found, the values in the data files are loaded into the column or columns. If no match is found, a set of NULL values for each record in the files is loaded into the table.

Note

• If additional non-matching columns are present in the data files, the values in these columns are not loaded.

• If additional non-matching columns are present in the target table, the COPY operation inserts NULL values into these columns. These columns must support NULL values.

• The COPY statement does not allow specifying a query to further transform the data during the load (i.e. COPY transformation).

NONE

The COPY operation loads the semi-structured data into a variant column or, if a query is included in the COPY statement, transforms the data.

Note

The following limitations currently apply:

• MATCH_BY_COLUMN_NAME cannot be used with the VALIDATION_MODE parameter in a COPY statement to validate the staged data rather than load it into the target table.

• Parquet data only. When MATCH_BY_COLUMN_NAME is set to CASE_SENSITIVE or CASE_INSENSITIVE, an empty column value (e.g. "col1": "") produces an error.

Default

NONE

ENFORCE_LENGTH = TRUE | FALSE

Use

Data loading only

Definition

Alternative syntax for TRUNCATECOLUMNS with reverse logic (for compatibility with other systems)

Boolean that specifies whether to truncate text strings that exceed the target column length:

• If TRUE, the COPY statement produces an error if a loaded string exceeds the target column length.

• If FALSE, strings are automatically truncated to the target column length.

This copy option supports CSV data, as well as string values in semi-structured data when loaded into separate columns in relational tables.

Note

• If the length of the target string column is set to the maximum (e.g. VARCHAR (16777216)), an incoming string cannot exceed this length; otherwise, the COPY command produces an error.

• This parameter is functionally equivalent to TRUNCATECOLUMNS, but has the opposite behavior. It is provided for compatibility with other databases. It is only necessary to include one of these two parameters in a COPY statement to produce the desired output.

Default

TRUE

TRUNCATECOLUMNS = TRUE | FALSE

Use

Data loading only

Definition

Alternative syntax for ENFORCE_LENGTH with reverse logic (for compatibility with other systems)

Boolean that specifies whether to truncate text strings that exceed the target column length:

• If TRUE, strings are automatically truncated to the target column length.

• If FALSE, the COPY statement produces an error if a loaded string exceeds the target column length.

This copy option supports CSV data, as well as string values in semi-structured data when loaded into separate columns in relational tables.

Note

• If the length of the target string column is set to the maximum (e.g. VARCHAR (16777216)), an incoming string cannot exceed this length; otherwise, the COPY command produces an error.

• This parameter is functionally equivalent to ENFORCE_LENGTH, but has the opposite behavior. It is provided for compatibility with other databases. It is only necessary to include one of these two parameters in a COPY statement to produce the desired output.

Default

FALSE

FORCE = TRUE | FALSE

Use

Data loading only

Definition

Boolean that specifies to load all files, regardless of whether they’ve been loaded previously and have not changed since they were loaded. Note that this option reloads files, potentially duplicating data in a table.

Default

FALSE

Access Control Requirements¶

A role used to execute this SQL command must have the following privileges at a minimum:

Note that operating on any object in a schema also requires the USAGE privilege on the parent database and schema.

For instructions on creating a custom role with a specified set of privileges, see Creating Custom Roles.

For general information about roles and privilege grants for performing SQL actions on securable objects, see Overview of Access Control.

Usage Notes¶

• A schema cannot contain tables and/or views with the same name. When creating a table:

  • If a view with the same name already exists in the schema, an error is returned and the table is not created.

  • If a table with the same name already exists in the schema, an error is returned and the table is not created, unless the optional OR REPLACE keyword is included in the command.

  Important

  Using OR REPLACE is the equivalent of using DROP TABLE on the existing table and then creating a new table with the same name; however, the dropped table is not permanently removed from the system. Instead, it is retained in Time Travel. This is important to note because dropped tables in Time Travel can be recovered, but they also contribute to data storage for your account. For more information, see Storage Costs for Time Travel and Fail-safe.

  CREATE OR REPLACE <object> statements are atomic. That is, when an object is replaced, the old object is deleted and the new object is created in a single transaction.

  This means that any queries concurrent with the CREATE OR REPLACE TABLE operation use either the old or new table version.

  Recreating or swapping a table drops its change data. Any stream on the table becomes stale. In addition, any stream on a view that has this table as an underlying table, becomes stale. A stale stream is unreadable.

• Similar to reserved keywords, ANSI-reserved function names (CURRENT_DATE, CURRENT_TIMESTAMP, etc.) cannot be used as column names.

• CREATE TABLE … CLONE:

  • If the source table has clustering keys, then the new table has clustering keys. By default, Automatic Clustering is suspended for the new table – even if Automatic Clustering was not suspended for the source table.

• CREATE TABLE … CHANGE_TRACKING = TRUE

  • When change tracking is enabled, the table is locked for the duration of the operation. Locks can cause latency with some associated DDL/DML operations. For more information, refer to Resource Locking.

• CREATE TABLE … LIKE:

  • If the source table has clustering keys, then the new table has clustering keys. By default, Automatic Clustering is not suspended for the new table – even if Automatic Clustering was suspended for the source table.

• CREATE TABLE … AS SELECT (CTAS):

  • If the aliases for the column names in the SELECT list are valid columns, then the column definitions are not required in the CTAS statement; if omitted, the column names and types are inferred from the underlying query:

    CREATE TABLE <table_name> AS SELECT ...
    

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    Alternatively, the names can be explicitly specified using the following syntax:

    CREATE TABLE <table_name> ( <col1_name> , <col2_name> , ... ) AS SELECT ...
    

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    The number of column names specified must match the number of SELECT list items in the query; the types of the columns are inferred from the types produced by the query.

  • When clustering keys are specified in a CTAS statement:

    • Column definitions are required and must be explicitly specified in the statement.

    • By default, Automatic Clustering is not suspended for the new table – even if Automatic Clustering is suspended for the source table.

  • If you want the table to be created with rows in a specific order, then use an ORDER BY sub-clause in the SELECT clause of the CTAS. Specifying CLUSTER BY does not cluster the data at the time that the table is created; instead, CLUSTER BY relies on automatic clustering to recluster the data over time.

    The ORDER BY sub-clause in a CREATE TABLE statement does not affect the order of the rows returned by future SELECT statements on that table. To specify the order of rows in future SELECT statements, use an ORDER BY sub-clause in those statements.

• Inside a transaction, any DDL statement (including CREATE TEMPORARY/TRANSIENT TABLE) commits the transaction before executing the DDL statement itself. The DDL statement then runs in its own transaction. The next statement after the DDL statement starts a new transaction. Therefore, you can’t create, use, and drop a temporary or transient table within a single transaction. If you want to use a temporary or transient table inside a transaction, then create the table before the transaction, and drop the table after the transaction.

• Recreating a table (using the optional OR REPLACE keyword) drops its history, which makes any stream on the table stale. A stale stream is unreadable.

• A single masking policy that uses conditional columns can be applied to multiple tables provided that the column structure of the table matches the columns specified in the policy.

• When creating a table with a masking policy on one or more table columns, or a row access policy added to the table, use the POLICY_CONTEXT function to simulate a query on the column(s) protected by a masking policy and the table protected by a row access policy.

• Regarding metadata:

  Attention

  Customers should ensure that no personal data (other than for a User object), sensitive data, export-controlled data, or other regulated data is entered as metadata when using the Snowflake service. For more information, see Metadata Fields in Snowflake.

Examples¶

Create a simple table in the current database and insert a row in the table:

CREATE TABLE mytable (amount NUMBER);

+-------------------------------------+
| status                              |
|-------------------------------------|
| Table MYTABLE successfully created. |
+-------------------------------------+

INSERT INTO mytable VALUES(1);

SHOW TABLES like 'mytable';

+---------------------------------+---------+---------------+-------------+-------+---------+------------+------+-------+--------------+----------------+
| created_on                      | name    | database_name | schema_name | kind  | comment | cluster_by | rows | bytes | owner        | retention_time |
|---------------------------------+---------+---------------+-------------+-------+---------+------------+------+-------+--------------+----------------|
| Mon, 11 Sep 2017 16:32:28 -0700 | MYTABLE | TESTDB        | PUBLIC      | TABLE |         |            |    1 |  1024 | ACCOUNTADMIN | 1              |
+---------------------------------+---------+---------------+-------------+-------+---------+------------+------+-------+--------------+----------------+

DESC TABLE mytable;

+--------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+
| name   | type         | kind   | null? | default | primary key | unique key | check | expression | comment |
|--------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------|
| AMOUNT | NUMBER(38,0) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
+--------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+

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Create a simple table and specify comments for both the table and the column in the table:

CREATE TABLE example (col1 NUMBER COMMENT 'a column comment') COMMENT='a table comment';

+-------------------------------------+
| status                              |
|-------------------------------------|
| Table EXAMPLE successfully created. |
+-------------------------------------+

SHOW TABLES LIKE 'example';

+---------------------------------+---------+---------------+-------------+-------+-----------------+------------+------+-------+--------------+----------------+
| created_on                      | name    | database_name | schema_name | kind  | comment         | cluster_by | rows | bytes | owner        | retention_time |
|---------------------------------+---------+---------------+-------------+-------+-----------------+------------+------+-------+--------------+----------------|
| Mon, 11 Sep 2017 16:35:59 -0700 | EXAMPLE | TESTDB        | PUBLIC      | TABLE | a table comment |            |    0 |     0 | ACCOUNTADMIN | 1              |
+---------------------------------+---------+---------------+-------------+-------+-----------------+------------+------+-------+--------------+----------------+

DESC TABLE example;

+------+--------------+--------+-------+---------+-------------+------------+-------+------------+------------------+
| name | type         | kind   | null? | default | primary key | unique key | check | expression | comment          |
|------+--------------+--------+-------+---------+-------------+------------+-------+------------+------------------|
| COL1 | NUMBER(38,0) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | a column comment |
+------+--------------+--------+-------+---------+-------------+------------+-------+------------+------------------+

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Create a table by selecting from an existing table:

CREATE TABLE mytable_copy (b) AS SELECT * FROM mytable;

DESC TABLE mytable_copy;

+------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+
| name | type         | kind   | null? | default | primary key | unique key | check | expression | comment |
|------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------|
| B    | NUMBER(38,0) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
+------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+

CREATE TABLE mytable_copy2 AS SELECT b+1 AS c FROM mytable_copy;

DESC TABLE mytable_copy2;

+------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+
| name | type         | kind   | null? | default | primary key | unique key | check | expression | comment |
|------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------|
| C    | NUMBER(39,0) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
+------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+

SELECT * FROM mytable_copy2;

+---+
| C |
|---|
| 2 |
+---+

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More advanced example of creating a table by selecting from an existing table; in this example, the values in the summary_amount column in the new table are derived from two columns in the source table:

CREATE TABLE testtable_summary (name, summary_amount) AS SELECT name, amount1 + amount2 FROM testtable;

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Create a table by selecting columns from a staged Parquet data file:

CREATE OR REPLACE TABLE parquet_col (
  custKey NUMBER DEFAULT NULL,
  orderDate DATE DEFAULT NULL,
  orderStatus VARCHAR(100) DEFAULT NULL,
  price VARCHAR(255)
)
AS SELECT
  $1:o_custkey::number,
  $1:o_orderdate::date,
  $1:o_orderstatus::text,
  $1:o_totalprice::text
FROM @my_stage;

+-----------------------------------------+
| status                                  |
|-----------------------------------------|
| Table PARQUET_COL successfully created. |
+-----------------------------------------+

DESC TABLE parquet_col;

+-------------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+
| name        | type         | kind   | null? | default | primary key | unique key | check | expression | comment |
|-------------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------|
| CUSTKEY     | NUMBER(38,0) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
| ORDERDATE   | DATE         | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
| ORDERSTATUS | VARCHAR(100) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
| PRICE       | VARCHAR(255) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
+-------------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+

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Create a table with the same column definitions as another table, but with no rows:

CREATE TABLE mytable (amount NUMBER);

INSERT INTO mytable VALUES(1);

SELECT * FROM mytable;

+--------+
| AMOUNT |
|--------|
|      1 |
+--------+

CREATE TABLE mytable_2 LIKE mytable;

DESC TABLE mytable_2;

+--------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+
| name   | type         | kind   | null? | default | primary key | unique key | check | expression | comment |
|--------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------|
| AMOUNT | NUMBER(38,0) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
+--------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+

SELECT * FROM mytable_2;

+--------+
| AMOUNT |
|--------|
+--------+

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Create a table with a multi-column clustering key:

CREATE TABLE mytable (date TIMESTAMP_NTZ, id NUMBER, content VARIANT) CLUSTER BY (date, id);

SHOW TABLES LIKE 'mytable';

+---------------------------------+---------+---------------+-------------+-------+---------+------------------+------+-------+--------------+----------------+
| created_on                      | name    | database_name | schema_name | kind  | comment | cluster_by       | rows | bytes | owner        | retention_time |
|---------------------------------+---------+---------------+-------------+-------+---------+------------------+------+-------+--------------+----------------|
| Mon, 11 Sep 2017 16:20:41 -0700 | MYTABLE | TESTDB        | PUBLIC      | TABLE |         | LINEAR(DATE, ID) |    0 |     0 | ACCOUNTADMIN | 1              |
+---------------------------------+---------+---------------+-------------+-------+---------+------------------+------+-------+--------------+----------------+

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Specify collation for columns in a table:

CREATE TABLE collation_demo (
  uncollated_phrase VARCHAR, 
  utf8_phrase VARCHAR COLLATE 'utf8',
  english_phrase VARCHAR COLLATE 'en',
  spanish_phrase VARCHAR COLLATE 'sp'
  );

INSERT INTO collation_demo (uncollated_phrase, utf8_phrase, english_phrase, spanish_phrase) 
   VALUES ('pinata', 'pinata', 'pinata', 'piñata');

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Create a table where the column definitions are derived from a set of staged files that contain Avro, Parquet, or ORC data.

Note that the mystage stage and my_parquet_format file format referenced in the statement must already exist. A set of files must already be staged in the cloud storage location referenced in the stage definition.

The following example creates a table using the detected schema from staged files and sorts the columns by order_id. It builds on an example in the INFER_SCHEMA topic.

CREATE TABLE mytable
  USING TEMPLATE (
    SELECT ARRAY_AGG(OBJECT_CONSTRUCT(*))
    WITHIN GROUP (ORDER BY order_id)
      FROM TABLE(
        INFER_SCHEMA(
          LOCATION=>'@mystage',
          FILE_FORMAT=>'my_parquet_format'
        )
      ));

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Note that sorting the columns by order_id only applies if all staged files share a single schema. If the set of staged data files includes multiple schemas with shared column names, the order represented in the order_id column might not match any single file.

Create a temporary table that is dropped automatically at the end of the session:

CREATE TEMPORARY TABLE demo_temporary (i INTEGER);
CREATE TEMP TABLE demo_temp (i INTEGER);

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For compatibility with other vendors, Snowflake also supports using the keywords below as synonyms for TEMPORARY:

CREATE LOCAL TEMPORARY TABLE demo_local_temporary (i INTEGER);
CREATE LOCAL TEMP TABLE demo_local_temp (i INTEGER);

CREATE GLOBAL TEMPORARY TABLE demo_global_temporary (i INTEGER);
CREATE GLOBAL TEMP TABLE demo_global_temp (i INTEGER);

CREATE VOLATILE TABLE demo_volatile (i INTEGER);

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