e3c8160433
### What changes were proposed in this pull request? ```SQL hive> create table t1(`a,` string); OK Time taken: 1.399 seconds hive> create table t2(`a,` string, b string); FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask. java.lang.RuntimeException: MetaException(message:org.apache.hadoop.hive.serde2.SerDeException org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe: columns has 3 elements while columns.types has 2 elements!) hive> create table t2(`a,` string, b string) stored as parquet; FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask. java.lang.IllegalArgumentException: ParquetHiveSerde initialization failed. Number of column name and column type differs. columnNames = [a, , b], columnTypes = [string, string] ``` It has a bug in Hive metastore. When users do not provide alias name in the SELECT query, we call `toPrettySQL` to generate the alias name. For example, the string `get_json_object(jstring, '$.f1')` will be the alias name for the function call in the statement ```SQL SELECT key, get_json_object(jstring, '$.f1') FROM tempView ``` Above is not an issue for the SELECT query statements. However, for CTAS, we hit the issue due to a bug in Hive metastore. Hive metastore does not like the column names containing commas and returned a confusing error message, like: ``` 17/04/26 23:12:56 ERROR [hive.log(397) -- main]: error in initSerDe: org.apache.hadoop.hive.serde2.SerDeException org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe: columns has 2 elements while columns.types has 1 elements! org.apache.hadoop.hive.serde2.SerDeException: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe: columns has 2 elements while columns.types has 1 elements! ``` Thus, this PR is to block users to create a table in Hive metastore when the table table has a column containing commas in the name. ### How was this patch tested? Added a test case Author: Xiao Li <gatorsmile@gmail.com> Closes #17781 from gatorsmile/blockIllegalColumnNames. |
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catalyst | ||
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hive | ||
hive-thriftserver | ||
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.