Minor Description
Mapping data frame field type to database column type is addressed to large extent by adding dialects, and Adding maxlength option in SPARK-10101 to set the VARCHAR length size.
In some cases it is hard to determine max supported VARCHAR size , For example DB2 Z/OS VARCHAR size depends on the page size. And some databases also has ROW SIZE limits for VARCHAR. Specifying default CLOB for all String columns will likely make read/write slow.
Allowing users to specify database type corresponding to the data frame field will be useful in cases where users wants to fine tune mapping for one or two fields, and is fine with default for all other fields .
I propose to make the following two properties available for users to set in the data frame metadata when writing to JDBC data sources.
database.column.type – column type to use for create table.
jdbc.column.type" – jdbc type to use for setting null values.
Example :
val secdf = sc.parallelize( Array(("Apple","Revenue ..."), ("Google","Income:123213"))).toDF("name", "report")
val metadataBuilder = new MetadataBuilder()
metadataBuilder.putString("database.column.type", "CLOB(100K)")
metadataBuilder.putLong("jdbc.type", java.sql.Types.CLOB)
val metadta = metadataBuilder.build()
val secReportDF = secdf.withColumn("report", col("report").as("report", metadata))
secReporrDF.write.jdbc("jdbc:mysql://<URL>/secdata", "reports", mysqlProps)
Attachments
Issue Links
- duplicates
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SPARK-11300 Support for string length when writing to JDBC
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- Resolved
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SPARK-10101 Spark JDBC writer mapping String to TEXT or VARCHAR
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- Resolved
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- links to
