spark-instrumented-optimizer/sql
Max Gekk bd26429931 [SPARK-31641][SQL] Fix days conversions by JSON legacy parser
### What changes were proposed in this pull request?
Perform days rebasing while converting days from JSON string field. In Spark 2.4 and earlier versions, the days are interpreted as days since the epoch in the hybrid calendar (Julian + Gregorian since 1582-10-15). Since Spark 3.0, the base calendar was switched to Proleptic Gregorian calendar, so, the days should be rebased to represent the same local date.

### Why are the changes needed?
The changes fix a bug and restore compatibility with Spark 2.4 in which:
```scala
scala> spark.read.schema("d date").json(Seq("{'d': '-141704'}").toDS).show
+----------+
|         d|
+----------+
|1582-01-01|
+----------+
```

### Does this PR introduce _any_ user-facing change?
Yes.

Before:
```scala
scala> spark.read.schema("d date").json(Seq("{'d': '-141704'}").toDS).show
+----------+
|         d|
+----------+
|1582-01-11|
+----------+
```

After:
```scala
scala> spark.read.schema("d date").json(Seq("{'d': '-141704'}").toDS).show
+----------+
|         d|
+----------+
|1582-01-01|
+----------+
```

### How was this patch tested?
Add a test to `JsonSuite`.

Closes #28453 from MaxGekk/json-rebase-legacy-days.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-05 14:15:31 +00:00
..
catalyst [SPARK-31641][SQL] Fix days conversions by JSON legacy parser 2020-05-05 14:15:31 +00:00
core [SPARK-31641][SQL] Fix days conversions by JSON legacy parser 2020-05-05 14:15:31 +00:00
hive [SPARK-31467][SQL][TEST] Refactor the sql tests to prevent TableAlreadyExistsException 2020-05-05 15:14:33 +09:00
hive-thriftserver [SPARK-31626][SQL] Port HIVE-10415: hive.start.cleanup.scratchdir configuration is not taking effect 2020-05-04 14:59:33 +09:00
create-docs.sh [SPARK-31550][SQL][DOCS] Set nondeterministic configurations with general meanings in sql configuration doc 2020-04-27 17:08:52 +09:00
gen-sql-api-docs.py [SPARK-31474][SQL][FOLLOWUP] Replace _FUNC_ placeholder with functionname in the note field of expression info 2020-04-23 13:33:04 +09:00
gen-sql-config-docs.py [SPARK-31550][SQL][DOCS] Set nondeterministic configurations with general meanings in sql configuration doc 2020-04-27 17:08:52 +09:00
gen-sql-functions-docs.py [SPARK-31562][SQL] Update ExpressionDescription for substring, current_date, and current_timestamp 2020-04-26 11:46:52 -07:00
mkdocs.yml [SPARK-30731] Update deprecated Mkdocs option 2020-02-19 17:28:58 +09:00
README.md [SPARK-30510][SQL][DOCS] Publicly document Spark SQL configuration options 2020-02-09 19:20:47 +09:00

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.