a2b3b67624
## What changes were proposed in this pull request? Replaced specific sequence encoders with generic sequence encoder to enable nesting of sequences. Does not add support for nested arrays as that cannot be solved in this way. ## How was this patch tested? ```bash build/mvn -DskipTests clean package && dev/run-tests ``` Additionally in Spark shell: ``` scala> Seq(Seq(Seq(1))).toDS.collect() res0: Array[Seq[Seq[Int]]] = Array(List(List(1))) ``` Author: Michal Senkyr <mike.senkyr@gmail.com> Closes #18011 from michalsenkyr/dataset-seq-nested. |
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catalyst | ||
core | ||
hive | ||
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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.