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https://issues.apache.org/jira/browse/FLINK-2828?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15258398#comment-15258398
]
ASF GitHub Bot commented on FLINK-2828:
---------------------------------------
Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/1939#discussion_r61120172
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/api/table/plan/nodes/dataset/BatchTableSourceScan.scala
---
@@ -0,0 +1,139 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.flink.api.table.plan.nodes.dataset
+
+import org.apache.calcite.plan._
+import org.apache.calcite.rel.RelNode
+import org.apache.calcite.rel.`type`.RelDataType
+import org.apache.calcite.rel.core.TableScan
+import org.apache.calcite.rel.metadata.RelMetadataQuery
+import org.apache.flink.api.common.functions.MapFunction
+import org.apache.flink.api.common.typeinfo.TypeInformation
+import org.apache.flink.api.java.DataSet
+import org.apache.flink.api.java.typeutils.PojoTypeInfo
+import org.apache.flink.api.table.BatchTableEnvironment
+import org.apache.flink.api.table.codegen.CodeGenerator
+import org.apache.flink.api.table.plan.schema.TableSourceTable
+import org.apache.flink.api.table.runtime.MapRunner
+import org.apache.flink.api.table.sources.BatchTableSource
+import
org.apache.flink.api.table.typeutils.TypeConverter.determineReturnType
+
+import scala.collection.JavaConversions._
+import scala.collection.JavaConverters._
+
+/** Flink RelNode to read data from an external source defined by a
[[BatchTableSource]]. */
+class BatchTableSourceScan(
--- End diff --
I agree, both classes share a lot of code, but another difference apart
from the unwrapping is that `DataSetScan` simply forwards its `DataSet` whereas
`BatchTableSourceScan` creates a new `DataSet` using the `BatchTableSource` and
the table environment. So I would like to keep separate classes, but it makes
sense to let them have a common abstract base class. What do you think?
Btw. `DataSetSource` was recently renamed to `DataSetScan` ;-)
> Add interfaces for Table API input formats
> ------------------------------------------
>
> Key: FLINK-2828
> URL: https://issues.apache.org/jira/browse/FLINK-2828
> Project: Flink
> Issue Type: New Feature
> Components: Table API
> Reporter: Timo Walther
> Assignee: Fabian Hueske
>
> In order to support input formats for the Table API, interfaces are
> necessary. I propose two types of TableSources:
> - AdaptiveTableSources can adapt their output to the requirements of the
> plan. Although the output schema stays the same, the TableSource can react on
> field resolution and/or predicates internally and can return adapted
> DataSet/DataStream versions in the "translate" step.
> - StaticTableSources are an easy way to provide the Table API with additional
> input formats without much implementation effort (e.g. for fromCsvFile())
> TableSources need to be deeply integrated into the Table API.
> The TableEnvironment requires a newly introduced AbstractExecutionEnvironment
> (common super class of all ExecutionEnvironments for DataSets and
> DataStreams).
> Here's what a TableSource can see from more complicated queries:
> {code}
> getTableJava(tableSource1)
> .filter("a===5 || a===6")
> .select("a as a4, b as b4, c as c4")
> .filter("b4===7")
> .join(getTableJava(tableSource2))
> .where("a===a4 && c==='Test' && c4==='Test2'")
> // Result predicates for tableSource1:
> // List("a===5 || a===6", "b===7", "c==='Test2'")
> // Result predicates for tableSource2:
> // List("c==='Test'")
> // Result resolved fields for tableSource1 (true = filtering,
> false=selection):
> // Set(("a", true), ("a", false), ("b", true), ("b", false), ("c", false),
> ("c", true))
> // Result resolved fields for tableSource2 (true = filtering,
> false=selection):
> // Set(("a", true), ("c", true))
> {code}
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