a4206d58e0
## What changes were proposed in this pull request? This is a followup of https://github.com/apache/spark/pull/20136 . #20136 didn't really work because in the test, we are using local backend, which shares the driver side `SparkEnv`, so `SparkEnv.get.executorId == SparkContext.DRIVER_IDENTIFIER` doesn't work. This PR changes the check to `TaskContext.get != null`, and move the check to `SQLConf.get`, and fix all the places that violate this check: * `InMemoryTableScanExec#createAndDecompressColumn` is executed inside `rdd.map`, we can't access `conf.offHeapColumnVectorEnabled` there. https://github.com/apache/spark/pull/21223 merged * `DataType#sameType` may be executed in executor side, for things like json schema inference, so we can't call `conf.caseSensitiveAnalysis` there. This contributes to most of the code changes, as we need to add `caseSensitive` parameter to a lot of methods. * `ParquetFilters` is used in the file scan function, which is executed in executor side, so we can't can't call `conf.parquetFilterPushDownDate` there. https://github.com/apache/spark/pull/21224 merged * `WindowExec#createBoundOrdering` is called on executor side, so we can't use `conf.sessionLocalTimezone` there. https://github.com/apache/spark/pull/21225 merged * `JsonToStructs` can be serialized to executors and evaluate, we should not call `SQLConf.get.getConf(SQLConf.FROM_JSON_FORCE_NULLABLE_SCHEMA)` in the body. https://github.com/apache/spark/pull/21226 merged ## How was this patch tested? existing test Author: Wenchen Fan <wenchen@databricks.com> Closes #21190 from cloud-fan/minor. |
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catalyst | ||
core | ||
hive | ||
hive-thriftserver | ||
create-docs.sh | ||
gen-sql-markdown.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 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 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
.