[GitHub] [incubator-iceberg] xabriel commented on a change in pull request #590: Allow spark.read.schema() to be set.

[GitBox <gi...@apache.org>]

xabriel commented on a change in pull request #590: Allow spark.read.schema() to be set.
URL: https://github.com/apache/incubator-iceberg/pull/590#discussion_r345939483
 
 

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 File path: spark/src/test/java/org/apache/iceberg/spark/source/TestSparkSchema.java
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+/*
+ * 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.iceberg.spark.source;
+
+import com.google.common.collect.Lists;
+import java.io.IOException;
+import java.util.List;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.iceberg.AssertHelpers;
+import org.apache.iceberg.PartitionSpec;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.hadoop.HadoopTables;
+import org.apache.iceberg.types.Types;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.types.DataTypes;
+import org.apache.spark.sql.types.Metadata;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+import org.junit.AfterClass;
+import org.junit.Assert;
+import org.junit.BeforeClass;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.rules.TemporaryFolder;
+
+import static org.apache.iceberg.types.Types.NestedField.optional;
+
+public class TestSparkSchema {
+
+  private static final Configuration CONF = new Configuration();
+  private static final Schema SCHEMA = new Schema(
+      optional(1, "id", Types.IntegerType.get()),
+      optional(2, "data", Types.StringType.get())
+  );
+  private static SparkSession spark = null;
+
+  @Rule
+  public TemporaryFolder temp = new TemporaryFolder();
+
+  @BeforeClass
+  public static void startSpark() {
+    TestSparkSchema.spark = SparkSession.builder().master("local[2]").getOrCreate();
+  }
+
+  @AfterClass
+  public static void stopSpark() {
+    SparkSession currentSpark = TestSparkSchema.spark;
+    TestSparkSchema.spark = null;
+    currentSpark.stop();
+  }
+
+  @Test
+  public void testSparkReadSchemaIsHonored() throws IOException {
+    String tableLocation = temp.newFolder("iceberg-table").toString();
+
+    HadoopTables tables = new HadoopTables(CONF);
+    PartitionSpec spec = PartitionSpec.unpartitioned();
+    tables.create(SCHEMA, spec, null, tableLocation);
+
+    List<SimpleRecord> expectedRecords = Lists.newArrayList(
+        new SimpleRecord(1, "a")
+    );
+    Dataset<Row> originalDf = spark.createDataFrame(expectedRecords, SimpleRecord.class);
+    originalDf.select("id", "data").write()
+        .format("iceberg")
+        .mode("append")
+        .save(tableLocation);
+
+    StructType sparkReadSchema =
+        new StructType(
+            new StructField[] {
+                new StructField("id", DataTypes.IntegerType, true, Metadata.empty())
+            }
+        );
+
+    Dataset<Row> resultDf = spark.read()
+        .schema(sparkReadSchema)
+        .format("iceberg")
+        .load(tableLocation);
+
+    Row[] results = (Row[]) resultDf.collect();
+
+    Assert.assertEquals("Result size matches", 1, results.length);
+    Assert.assertEquals("Row length matches with sparkReadSchema", 1, results[0].length());
+    Assert.assertEquals("Row content matches data", 1, results[0].getInt(0));
+  }
+
+  @Test
+  public void testEmptyRowsIfSparkReadSchemaIsOff() throws IOException {
+    String tableLocation = temp.newFolder("iceberg-table").toString();
+
+    HadoopTables tables = new HadoopTables(CONF);
+    PartitionSpec spec = PartitionSpec.unpartitioned();
+    tables.create(SCHEMA, spec, null, tableLocation);
+
+    List<SimpleRecord> expectedRecords = Lists.newArrayList(
+        new SimpleRecord(1, "a")
+    );
+    Dataset<Row> originalDf = spark.createDataFrame(expectedRecords, SimpleRecord.class);
+    originalDf.select("id", "data").write()
+        .format("iceberg")
+        .mode("append")
+        .save(tableLocation);
+
+    StructType sparkReadSchema =
+        new StructType(
+            new StructField[] {
+                new StructField("idd", DataTypes.IntegerType, true, Metadata.empty()) // wrong field name
+            }
+        );
+
+    Dataset<Row> resultDf = spark.read()
+        .schema(sparkReadSchema)
+        .format("iceberg")
+        .load(tableLocation);
+
+    Row[] results = (Row[]) resultDf.collect();
+
+    Assert.assertEquals("Result size matches", 1, results.length);
+    Assert.assertEquals("Row length matches with sparkReadSchema", 0, results[0].length());
 
 Review comment:
   Done.

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