Github user twalthr commented on a diff in the pull request:
https://github.com/apache/flink/pull/1559#discussion_r51241130
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/api/java/table/JavaBatchTranslator.scala
---
@@ -41,21 +44,13 @@ class JavaBatchTranslator extends PlanTranslator {
// create table representation from DataSet
val dataSetTable = new DataSetTable[A](
- repr.asInstanceOf[JavaDataSet[A]],
- fieldNames
+ repr.asInstanceOf[JavaDataSet[A]],
+ fieldNames
)
-
- // register table in Cascading schema
- val schema = Frameworks.createRootSchema(true)
val tableName = repr.hashCode().toString
- schema.add(tableName, dataSetTable)
- // initialize RelBuilder
- val frameworkConfig = Frameworks
- .newConfigBuilder
- .defaultSchema(schema)
- .build
- val relBuilder = RelBuilder.create(frameworkConfig)
+ TranslationContext.addDataSet(tableName, dataSetTable)
--- End diff --
Do we really want to have this static? What happens if we use
multipleTableEnvironments in our program? They shouldn't influence each other.
Is the hash code really unique? In the old Table API we had a AtomicCounter
that guaranted uniqueness.
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