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https://issues.apache.org/jira/browse/SPARK-25198?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16589547#comment-16589547
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Liang-Chi Hsieh commented on SPARK-25198:
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I think the {{customSchema}} here refers to Spark's Catalyst SQL datatypes, not
Postgres datatypes. For Postgres json column, string type column should be
mapped to it. Doesn't it work?
> org.apache.spark.sql.catalyst.parser.ParseException: DataType json is not
> supported.
> ------------------------------------------------------------------------------------
>
> Key: SPARK-25198
> URL: https://issues.apache.org/jira/browse/SPARK-25198
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.3.1
> Environment: Ubuntu 18.04, Spark 2.3.1,
> org.postgresql:postgresql:42.2.4
> Reporter: antonkulaga
> Priority: Major
>
> Whenever I try to save the dataframe with one of the columns with JSON string
> inside to the latest Postgres I get
> org.apache.spark.sql.catalyst.parser.ParseException: DataType json is not
> supported. As Postgres supports JSON well and I use the latest postgresql
> client I expect it to work. Here is an example of the code that crashes
> val columnTypes = """id integer, parameters json, title text, gsm text, gse
> text, organism text, characteristics text, molecule text, model text,
> description text, treatment_protocol text, extract_protocol text, source_name
> text,data_processing text, submission_date text,last_update_date text, status
> text, type text, contact text, gpl text"""
> myDataframe.write.format("jdbc").option("url",
> "jdbc:postgresql://db/sequencing").option("customSchema",
> columnTypes).option("dbtable", "test").option("user",
> "postgres").option("password", "changeme").save()
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