15557a7d05
### What changes were proposed in this pull request? When encoding Java Beans to Spark DataFrame, respecting `javax.annotation.Nonnull` and producing non-null fields. ### Why are the changes needed? When encoding Java Beans to Spark DataFrame, non-primitive types are encoded as nullable fields. Although It works for most cases, it can be an issue under a few situations, e.g. the one described in the JIRA ticket when saving DataFrame to Avro format with non-null field. We should allow Spark users more flexibility when creating Spark DataFrame from Java Beans. Currently, Spark users cannot create DataFrame with non-nullable fields in the schema from beans with non-nullable properties. Although it is possible to project top-level columns with SQL expressions like `AssertNotNull` to make it non-null, for nested fields it is more tricky to do it similarly. ### Does this PR introduce any user-facing change? Yes. After this change, Spark users can use `javax.annotation.Nonnull` to annotate non-null fields in Java Beans when encoding beans to Spark DataFrame. ### How was this patch tested? Added unit test. Closes #27851 from viirya/SPARK-31071. Authored-by: Liang-Chi Hsieh <viirya@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com> |
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.. | ||
catalyst | ||
core | ||
hive | ||
hive-thriftserver | ||
create-docs.sh | ||
gen-sql-api-docs.py | ||
gen-sql-config-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.