Specifies the format of the external or web table data.
| Valid in: | DATA and PROC steps (when accessing DBMS data using SAS/ACCESS software) |
|---|---|
| Categories: | Bulk Loading |
| Data Set Control | |
| Default: | TEXT [Greenplum, Hadoop, HAWQ, Spark in HDFS, Yellowbrick] |
| CSV [PostgreSQL, Spark in Databricks] | |
| Requirement: | To specify this option, you must first specify BULKLOAD=YES. |
| Data source: | Greenplum, Hadoop, HAWQ, PostgreSQL, Spark, Yellowbrick |
| Notes: | Support for Yellowbrick was added in SAS 9.4M7. |
| Support for Hadoop was added in SAS 9.4M8. | |
| Support for Spark was added in SAS 9.4M9. | |
| The Parquet format was added in SAS 9.4M9. | |
| See: | BL_DELIMITER= data set option, BL_FORCE_NOT_NULL= data set option, BL_NULL= data set option, BL_QUOTE= data set option, BULKLOAD= data set option |
Table of Contents
specifies a comma-separated value format.
specifies the Apache ORC (Optimized Row Columnar) open-source file format.
| Restriction | ORC format is supported only for Hadoop. |
|---|
specifies the Apache Parquet open-source file format.
| Note | Parquet is supported only for Hadoop. |
|---|
specifies plain text format.
In Hadoop and Spark, this option controls the format of the bulk load staging file. The Hadoop engine and the Spark engine (when bulk loading to HDFS) do not support other bulk loading data set options for the staging file.
Spark: This option is used when the Spark engine bulk loads or bulk unloads data in Databricks. For more information, see Bulk Loading and Unloading to Databricks in Azure.