You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Xiao Li (JIRA)" <ji...@apache.org> on 2018/06/26 22:18:00 UTC
[jira] [Resolved] (SPARK-24423) Add a new option `query` for JDBC
sources
[ https://issues.apache.org/jira/browse/SPARK-24423?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Xiao Li resolved SPARK-24423.
-----------------------------
Resolution: Fixed
Assignee: Dilip Biswal
Fix Version/s: 2.4.0
> Add a new option `query` for JDBC sources
> -----------------------------------------
>
> Key: SPARK-24423
> URL: https://issues.apache.org/jira/browse/SPARK-24423
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.3.0
> Reporter: Xiao Li
> Assignee: Dilip Biswal
> Priority: Major
> Fix For: 2.4.0
>
>
> Currently, our JDBC connector provides the option `dbtable` for users to specify the to-be-loaded JDBC source table.
> {code}
> val jdbcDf = spark.read
> .format("jdbc")
> .option("*dbtable*", "dbName.tableName")
> .options(jdbcCredentials: Map)
> .load()
> {code}
> Normally, users do not fetch the whole JDBC table due to the poor performance/throughput of JDBC. Thus, they normally just fetch a small set of tables. For advanced users, they can pass a subquery as the option.
> {code}
> val query = """ (select * from tableName limit 10) as tmp """
> val jdbcDf = spark.read
> .format("jdbc")
> .option("*dbtable*", query)
> .options(jdbcCredentials: Map)
> .load()
> {code}
> However, this is straightforward to end users. We should simply allow users to specify the query by a new option `query`. We will handle the complexity for them.
> {code}
> val query = """select * from tableName limit 10"""
> val jdbcDf = spark.read
> .format("jdbc")
> .option("*{color:#ff0000}query{color}*", query)
> .options(jdbcCredentials: Map)
> .load()
> {code}
> Users are not allowed to specify query and dbtable at the same time.
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org