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https://issues.apache.org/jira/browse/SPARK-16552?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15378277#comment-15378277
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Apache Spark commented on SPARK-16552:
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User 'gatorsmile' has created a pull request for this issue:
https://github.com/apache/spark/pull/14207
> Store the Inferred Schemas into External Catalog Tables when Creating Tables
> ----------------------------------------------------------------------------
>
> Key: SPARK-16552
> URL: https://issues.apache.org/jira/browse/SPARK-16552
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.0.0
> Reporter: Xiao Li
>
> Currently, in Spark SQL, the initial creation of schema can be classified
> into two groups. It is applicable to both Hive tables and Data Source tables:
> Group A. Users specify the schema.
> Case 1 CREATE TABLE AS SELECT: the schema is determined by the result schema
> of the SELECT clause. For example,
> {noformat}
> CREATE TABLE tab STORED AS TEXTFILE
> AS SELECT * from input
> {noformat}
> Case 2 CREATE TABLE: users explicitly specify the schema. For example,
> {noformat}
> CREATE TABLE jsonTable (_1 string, _2 string)
> USING org.apache.spark.sql.json
> {noformat}
> Group B. Spark SQL infer the schema at runtime.
> Case 3 CREATE TABLE. Users do not specify the schema but the path to the file
> location. For example,
> {noformat}
> CREATE TABLE jsonTable
> USING org.apache.spark.sql.json
> OPTIONS (path '${tempDir.getCanonicalPath}')
> {noformat}
> Now, Spark SQL does not store the inferred schema in the external catalog for
> the cases in Group B. When users refreshing the metadata cache, accessing the
> table at the first time after (re-)starting Spark, Spark SQL will infer the
> schema and store the info in the metadata cache for improving the performance
> of subsequent metadata requests. However, the runtime schema inference could
> cause undesirable schema changes after each reboot of Spark.
> It is desirable to store the inferred schema in the external catalog when
> creating the table. When users intend to refresh the schema, they issue
> `REFRESH TABLE`. Spark SQL will infer the schema again based on the
> previously specified table location and update/refresh the schema in the
> external catalog and metadata cache.
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