9b9db5a8a0
### What changes were proposed in this pull request? This PR fixes an issue that `from_json` and `to_json` cannot handle `timestamp_ntz` type properly. In the current master, `from_json`/`to_json` can handle `timestamp` type like as follows. ``` SELECT from_json('{"a":"2021-11-23 11:22:33"}', "a TIMESTAMP"); {"a":2021-11-23 11:22:33} ``` ``` SELECT to_json(map("a", TIMESTAMP"2021-11-23 11:22:33")); {"a":"2021-11-23T11:22:33.000+09:00"} ``` But they cannot handle `timestamp_ntz` type properly. ``` SELECT from_json('{"a":"2021-11-23 11:22:33"}', "a TIMESTAMP_NTZ"); 21/08/12 16:16:00 ERROR SparkSQLDriver: Failed in [SELECT from_json('{"a":"2021-11-23 11:22:33"}', "a TIMESTAMP_NTZ")] java.lang.Exception: Unsupported type: timestamp_ntz at org.apache.spark.sql.errors.QueryExecutionErrors$.unsupportedTypeError(QueryExecutionErrors.scala:777) at org.apache.spark.sql.catalyst.json.JacksonParser.makeConverter(JacksonParser.scala:339) at org.apache.spark.sql.catalyst.json.JacksonParser.$anonfun$makeConverter$17(JacksonParser.scala:313) ``` ``` SELECT to_json(map("a", TIMESTAMP_NTZ"2021-11-23 11:22:33")); 21/08/12 16:14:07 ERROR SparkSQLDriver: Failed in [SELECT to_json(map("a", TIMESTAMP_NTZ"2021-11-23 11:22:33"))] java.lang.RuntimeException: Failed to convert value 1637666553000000 (class of class java.lang.Long) with the type of TimestampNTZType to JSON. at org.apache.spark.sql.errors.QueryExecutionErrors$.failToConvertValueToJsonError(QueryExecutionErrors.scala:294) at org.apache.spark.sql.catalyst.json.JacksonGenerator.$anonfun$makeWriter$25(JacksonGenerator.scala:201) at org.apache.spark.sql.catalyst.json.JacksonGenerator.$anonfun$makeWriter$25$adapted(JacksonGenerator.scala:199) at org.apache.spark.sql.catalyst.json.JacksonGenerator.writeMapData(JacksonGenerator.scala:253) at org.apache.spark.sql.catalyst.json.JacksonGenerator.$anonfun$write$3(JacksonGenerator.scala:293) at org.apache.spark.sql.catalyst.json.JacksonGenerator.writeObject(JacksonGenerator.scala:206) at org.apache.spark.sql.catalyst.json.JacksonGenerator.write(JacksonGenerator.scala:292) ``` ### Why are the changes needed? Bug fix. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? New test. Closes #33742 from sarutak/json-ntz. Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com> Signed-off-by: Max Gekk <max.gekk@gmail.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.