f3ed62a381
### What changes were proposed in this pull request? Currently, we have a bug when we specify `IF NOT EXISTS` in `INSERT OVERWRITE` data source tables. For example, given a query: ```SQL INSERT OVERWRITE TABLE $tableName partition (b=2, c=3) IF NOT EXISTS SELECT 9, 10 ``` we will get the following error: ``` unresolved operator 'InsertIntoTable Relation[a#425,d#426,b#427,c#428] parquet, Map(b -> Some(2), c -> Some(3)), true, true;; 'InsertIntoTable Relation[a#425,d#426,b#427,c#428] parquet, Map(b -> Some(2), c -> Some(3)), true, true +- Project [cast(9#423 as int) AS a#429, cast(10#424 as int) AS d#430] +- Project [9 AS 9#423, 10 AS 10#424] +- OneRowRelation$ ``` This PR is to fix the issue to follow the behavior of Hive serde tables > INSERT OVERWRITE will overwrite any existing data in the table or partition unless IF NOT EXISTS is provided for a partition ### How was this patch tested? Modified an existing test case Author: gatorsmile <gatorsmile@gmail.com> Closes #18050 from gatorsmile/insertPartitionIfNotExists. |
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catalyst | ||
core | ||
hive | ||
hive-thriftserver | ||
README.md |
Spark SQL
This module provides support for executing relational queries expressed in either SQL or the DataFrame/Dataset API.
Spark SQL is broken up into four subprojects:
- Catalyst (sql/catalyst) - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
- Execution (sql/core) - A query planner / execution engine for translating Catalyst's logical query plans into Spark RDDs. This component also includes a new public interface, SQLContext, that allows users to execute SQL or LINQ statements against existing RDDs and Parquet files.
- Hive Support (sql/hive) - Includes an extension of SQLContext called HiveContext that allows users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allows users to run queries that include Hive UDFs, UDAFs, and UDTFs.
- HiveServer and CLI support (sql/hive-thriftserver) - Includes support for the SQL CLI (bin/spark-sql) and a HiveServer2 (for JDBC/ODBC) compatible server.