![]() ![]() In SQL Server Management Studio, open Object Explorer, expand Server Objects,.How to create a SQL Server Linked Server to Amazon Redshift To the Amazon Redshift database, you will see the following message: Connection Use the port that the cluster was configured to use when it was launched. By default, Amazon Redshift uses port 5439, but you should In the Amazon Redshift console on the cluster’s details page. ![]() For example, to create a remark for a specific table column following SQL statement can be used: "comment on column RedshiftTable.Specify the endpoint for your Amazon Redshift cluster. Remarks is the comment text created for the column. It is interesting that inverval data type is not supported within Amazon Redshift tables, but it is listed in SVV_COLUMNS system view. Interval_precision shows the interval precision. It is the second argument used while creating a decimal data type.ĭatetime_precision indicates the datetime precision For integer values this is 2 and for decimal values it is 10. Numeric_precision_radix shows the numeric precision radix. (SmallInt:16, Int:32, BigInt:64, for decimals it is the first argument in definition) Numeric_precision for columns with numberic data types, shows the numeric precision. Is_nullable identifies if column accepts NULL values or not by YES/NO valueĭata_type shows the table column's data typeĬharacter_maximum_length shows the maximum number of character values allowed for the column For example, if the table is created using SQL code "create table redshifttable (code varchar(5) default 'AAAAA') " the column_default value will be "'AAAAA'::character varying" So it cannot be used directly as the default value. The column default text includes the data type identifiers for character data types. On the other hand, using the ordinal position the automatic code generation processes can be built.Ĭolumn_default shows the default value if the table DDL is created with a default value for the column definition. Considering the columnar storage of Amazon Redshift architecture, this does not provide a useful information. Ordinal_position shows the position of the column in the table definition. Table_name is the name of the table where we filter for columns of itĬolumn_name is the name of the table column we queried for ![]() Table_schema is the schema name where the table is created under Table_catalog is the database name where the table is created ![]() The SVV_COLUMNS system view has more details about each table column then the catalog view PG_TABLE_DEF SELECT * FROM SVV_COLUMNS WHERE upper("table_name") = upper('Category') Here is a sample SQL query that can be executed to get all columns details of a Redshift table. Information_Schema.Columns for Redshift Table Columns DetailsĪnother useful system view for querying table columns on a Redshift database is Information_Schema.Columns view. Notnull column value is true if the column is created by using a NOT NULL constraint Otherwise, the column is either part of a compound sort key or interleaved sort key If it is 0, then this column is not a sort key for the table. For a complete list of Amazon Redshift Compression Encodings, you can refer to Database Developer Guideĭistkey is true if the column is used as a Distributio Key for that database table For the Amazon Redshift database data types, Amazon Redshift's Data types page can be referred.Įncoding indicates the compression encoding settings for that column. Type shows the data type name like integer, date, timestamp, etc. Schemaname is the name of the schema that target table is created under.Ĭolumn shows the column name in a specific table The returned data for table columns contains following columns from PG_TABLE_DEF catalog table SELECT * FROM PG_TABLE_DEF WHERE upper(tablename) = upper('Category') SELECT * FROM PG_TABLE_DEF WHERE lower(tablename) = lower('Category') ![]()
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