f8bf72ed5d
### What changes were proposed in this pull request? Invoke `CatalogImpl.refreshTable()` instead of `SessionCatalog.refreshTable` in v1 implementation of the `LOAD DATA` command. `SessionCatalog.refreshTable` just refreshes metadata comparing to `CatalogImpl.refreshTable()` which refreshes cached table data as well. ### Why are the changes needed? The example below portraits the issue: - Create a source table: ```sql spark-sql> CREATE TABLE src_tbl (c0 int, part int) USING hive PARTITIONED BY (part); spark-sql> INSERT INTO src_tbl PARTITION (part=0) SELECT 0; spark-sql> SHOW TABLE EXTENDED LIKE 'src_tbl' PARTITION (part=0); default src_tbl false Partition Values: [part=0] Location: file:/Users/maximgekk/proj/load-data-refresh-cache/spark-warehouse/src_tbl/part=0 ... ``` - Load data from the source table to a cached destination table: ```sql spark-sql> CREATE TABLE dst_tbl (c0 int, part int) USING hive PARTITIONED BY (part); spark-sql> INSERT INTO dst_tbl PARTITION (part=1) SELECT 1; spark-sql> CACHE TABLE dst_tbl; spark-sql> SELECT * FROM dst_tbl; 1 1 spark-sql> LOAD DATA LOCAL INPATH '/Users/maximgekk/proj/load-data-refresh-cache/spark-warehouse/src_tbl/part=0' INTO TABLE dst_tbl PARTITION (part=0); spark-sql> SELECT * FROM dst_tbl; 1 1 ``` The last query does not return new loaded data. ### Does this PR introduce _any_ user-facing change? Yes. After the changes, the example above works correctly: ```sql spark-sql> LOAD DATA LOCAL INPATH '/Users/maximgekk/proj/load-data-refresh-cache/spark-warehouse/src_tbl/part=0' INTO TABLE dst_tbl PARTITION (part=0); spark-sql> SELECT * FROM dst_tbl; 0 0 1 1 ``` ### How was this patch tested? Added new test to `org.apache.spark.sql.hive.CachedTableSuite`: ``` $ build/sbt -Phive -Phive-thriftserver "test:testOnly *CachedTableSuite" ``` Closes #31304 from MaxGekk/load-data-refresh-cache. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com> |
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| .. | ||
| catalyst | ||
| core | ||
| hive | ||
| hive-thriftserver | ||
| create-docs.sh | ||
| gen-sql-api-docs.py | ||
| gen-sql-config-docs.py | ||
| gen-sql-functions-docs.py | ||
| mkdocs.yml | ||
| 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 extensions that allow users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allow 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.
Running ./sql/create-docs.sh generates SQL documentation for built-in functions under sql/site, and SQL configuration documentation that gets included as part of configuration.md in the main docs directory.