Dimitris Tsirogiannis 9f497ba02f IMPALA-2890: Support ALTER TABLE statements for Kudu tables
With this commit, we add support for additional ALTER TABLE statements
against Kudu tables. The new supported ALTER TABLE operations for Kudu are:
- ADD/DROP range partitions. Syntax:
    ALTER TABLE <tbl_name> ADD [IF NOT EXISTS] RANGE <kudu_partition_spec>
    ALTER TABLE <tbl_name> DROP [IF EXISTS] RANGE <kudu_partition_spec>
- ADD/DROP/RENAME column. Syntax:
    ALTER TABLE <tbl_name> ADD COLUMNS (col_spec, [col_spec, ...])
    ALTER TABLE <tbl_name> DROP COLUMN <col_name>
    ALTER TABLE <tbl_name> CHANGE COLUMN <old> <new_name> <type>
- Rename Kudu table using the 'kudu.table_name' table property. Example:
  ALTER TABLE <tbl_name> SET TBLPROPERTY ('kudu.tbl_name'='<new_name>'),
  will change the underlying Kudu table name to <new_name>.
- Renaming the HMS/Catalog table entry of a Kudu table is supported using the
  existing ALTER TABLE <tbl_name> RENAME TO <new_tbl_name> syntax.

Not supported:
- ALTER TABLE <tbl_name> REPLACE COLUMNS

Change-Id: I04bc87e04e05da5cc03edec79d13cedfd2012896
Reviewed-on: http://gerrit.cloudera.org:8080/5136
Reviewed-by: Dimitris Tsirogiannis <dtsirogiannis@cloudera.com>
Tested-by: Internal Jenkins
2016-11-30 04:55:03 +00:00

Welcome to Impala

Lightning-fast, distributed SQL queries for petabytes of data stored in Apache Hadoop clusters.

Impala is a modern, massively-distributed, massively-parallel, C++ query engine that lets you analyze, transform and combine data from a variety of data sources:

  • Best of breed performance and scalability.
  • Support for data stored in HDFS, Apache HBase and Amazon S3.
  • Wide analytic SQL support, including window functions and subqueries.
  • On-the-fly code generation using LLVM to generate CPU-efficient code tailored specifically to each individual query.
  • Support for the most commonly-used Hadoop file formats, including the Apache Parquet (incubating) project.
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