Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22009#discussion_r208808788
--- Diff:
sql/core/src/main/java/org/apache/spark/sql/sources/v2/reader/ReadSupport.java
---
@@ -0,0 +1,53 @@
+/*
+ * 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.spark.sql.sources.v2.reader;
+
+import org.apache.spark.annotation.InterfaceStability;
+import org.apache.spark.sql.types.StructType;
+
+/**
+ * The base interface for all the batch and streaming read supports. Data
sources should implement
+ * concrete read support interfaces like {@link BatchReadSupport}.
+ */
[email protected]
+public interface ReadSupport {
+
+ /**
+ * Returns the full schema of this data source, which is usually the
physical schema of the
+ * underlying storage. This full schema should not be affected by column
pruning or other
+ * optimizations.
+ *
+ * If this method fails (by throwing an exception), the action will fail
and no Spark job will be
+ * submitted.
+ */
+ StructType fullSchema();
--- End diff --
This is needed for both batch and streaming.
For streaming source, it must have a consistent schema across epochs. So
the `fullSchema` should be defined in `ReadSupport` not `ScanConfig`. Each
epoch may have different `readSchema` though, assuming different epochs can
apply column pruning differently.
For batch, Spark needs the data source to report schema before any
optimization happens, at that time the `ScanConfig` is not created yet.
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