DROP TABLE Statement

Removes an Impala table. Also removes the underlying HDFS data files for internal tables, although not for external tables.

Syntax:

DROP TABLE [IF EXISTS] [db_name.]table_name [PURGE]

IF EXISTS clause:

The optional IF EXISTS clause makes the statement succeed whether or not the table exists. If the table does exist, it is dropped; if it does not exist, the statement has no effect. This capability is useful in standardized setup scripts that remove existing schema objects and create new ones. By using some combination of IF EXISTS for the DROP statements and IF NOT EXISTS clauses for the CREATE statements, the script can run successfully the first time you run it (when the objects do not exist yet) and subsequent times (when some or all of the objects do already exist).

PURGE clause:

The optional PURGE keyword, available in Impala 2.3 and higher, causes Impala to remove the associated HDFS data files immediately, rather than going through the HDFS trashcan mechanism. Use this keyword when dropping a table if it is crucial to remove the data as quickly as possible to free up space, or if there is a problem with the trashcan, such as the trash cannot being configured or being in a different HDFS encryption zone than the data files.

Statement type: DDL

Usage notes:

By default, Impala removes the associated HDFS directory and data files for the table. If you issue a DROP TABLE and the data files are not deleted, it might be for the following reasons:

If the table was created with the EXTERNAL clause, Impala leaves all files and directories untouched. Use external tables when the data is under the control of other Hadoop components, and Impala is only used to query the data files from their original locations.
Impala might leave the data files behind unintentionally, if there is no HDFS location available to hold the HDFS trashcan for the impala user. See User Account Requirements for the procedure to set up the required HDFS home directory.

Make sure that you are in the correct database before dropping a table, either by issuing a USE statement first or by using a fully qualified name db_name.table_name.

If you intend to issue a DROP DATABASE statement, first issue DROP TABLE statements to remove all the tables in that database.

Examples:

create database temporary;
use temporary;
create table unimportant (x int);
create table trivial (s string);
-- Drop a table in the current database.
drop table unimportant;
-- Switch to a different database.
use default;
-- To drop a table in a different database...
drop table trivial;
ERROR: AnalysisException: Table does not exist: default.trivial
-- ...use a fully qualified name.
drop table temporary.trivial;

For other tips about managing and reclaiming Impala disk space, see Managing Disk Space for Impala Data.

Amazon S3 considerations:

The DROP TABLE statement can remove data files from S3 if the associated S3 table is an internal table. In Impala 2.6 and higher, as part of improved support for writing to S3, Impala also removes the associated folder when dropping an internal table that resides on S3. See Using Impala with Amazon S3 Object Store for details about working with S3 tables.

For best compatibility with the S3 write support in Impala 2.6 and higher:

Use native Hadoop techniques to create data files in S3 for querying through Impala.
Use the PURGE clause of DROP TABLE when dropping internal (managed) tables.

By default, when you drop an internal (managed) table, the data files are moved to the HDFS trashcan. This operation is expensive for tables that reside on the Amazon S3 object store. Therefore, for S3 tables, prefer to use

DROP TABLE table_name
          PURGE

rather than the default DROP TABLE statement. The PURGE clause makes Impala delete the data files immediately, skipping the HDFS trashcan. For the PURGE clause to work effectively, you must originally create the data files on S3 using one of the tools from the Hadoop ecosystem, such as hadoop fs -cp, or INSERT in Impala or Hive.

In Impala 2.6 and higher, Impala DDL statements such as CREATE DATABASE, CREATE TABLE, DROP DATABASE CASCADE, DROP TABLE, and ALTER TABLE [ADD|DROP] PARTITION can create or remove folders as needed in the Amazon S3 system. Prior to Impala 2.6, you had to create folders yourself and point Impala database, tables, or partitions at them, and manually remove folders when no longer needed. See Using Impala with Amazon S3 Object Store for details about reading and writing S3 data with Impala.

Cancellation: Cannot be cancelled.

HDFS permissions:

For an internal table, the user ID that the impalad daemon runs under, typically the impala user, must have write permission for all the files and directories that make up the table.

For an external table, dropping the table only involves changes to metadata in the metastore database. Because Impala does not remove any HDFS files or directories when external tables are dropped, no particular permissions are needed for the associated HDFS files or directories.

Kudu considerations:

Kudu tables can be managed or external, the same as with HDFS-based tables. For a managed table, the underlying Kudu table and its data are removed by DROP TABLE. For an external table, the underlying Kudu table and its data remain after a DROP TABLE.

Related information:

Overview of Impala Tables, ALTER TABLE Statement, CREATE TABLE Statement, Partitioning for Impala Tables, Internal Tables, External Tables