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Posted to issues@spark.apache.org by "Xiao Li (JIRA)" <ji...@apache.org> on 2018/05/30 06:41:00 UTC
[jira] [Updated] (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 updated SPARK-24423:
----------------------------
Description:
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.
was:
Currently, our JDBC connector provides the option `dbtable` for users to specify the to-be-loaded JDBC source table.
val jdbcDf = spark.read
.format("jdbc")
.option("*dbtable*", "dbName.tableName")
.options(jdbcCredentials: Map)
.load()
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.
val query = """ (select * from tableName limit 10) as tmp """
val jdbcDf = spark.read
.format("jdbc")
.option("*dbtable*", query)
.options(jdbcCredentials: Map)
.load()
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.
val query = """select * from tableName limit 10"""
val jdbcDf = spark.read
.format("jdbc")
.option("*{color:#ff0000}query{color}*", query)
.options(jdbcCredentials: Map)
.load()
Users are not allowed to specify query and dbtable at the same time.
> 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
> Priority: Major
>
> 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.
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