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Subject [GitHub] [incubator-hudi] yihua commented on a change in pull request #1165: [HUDI-76] Add CSV Source support for Hudi Delta Streamer
Date Wed, 11 Mar 2020 06:15:18 GMT
yihua commented on a change in pull request #1165: [HUDI-76] Add CSV Source support for Hudi
Delta Streamer
URL: https://github.com/apache/incubator-hudi/pull/1165#discussion_r390760597
 
 

 ##########
 File path: hudi-utilities/src/main/java/org/apache/hudi/utilities/sources/CsvDFSSource.java
 ##########
 @@ -0,0 +1,125 @@
+/*
+ * 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.hudi.utilities.sources;
+
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.common.util.TypedProperties;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.utilities.schema.SchemaProvider;
+import org.apache.hudi.utilities.sources.helpers.DFSPathSelector;
+
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.sql.DataFrameReader;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.avro.SchemaConverters;
+import org.apache.spark.sql.types.StructType;
+
+import java.util.Arrays;
+import java.util.List;
+
+/**
+ * Reads data from CSV files on DFS as the data source.
+ *
+ * Internally, we use Spark to read CSV files thus any limitation of Spark CSV also applies
here
+ * (e.g., limited support for nested schema).
+ *
+ * You can set the CSV-specific configs in the format of hoodie.deltastreamer.csv.*
+ * that are Spark compatible to deal with CSV files in Hudi.  The supported options are:
+ *
+ *       "sep", "encoding", "quote", "escape", "charToEscapeQuoteEscaping", "comment",
+ *       "header", "enforceSchema", "inferSchema", "samplingRatio", "ignoreLeadingWhiteSpace",
+ *       "ignoreTrailingWhiteSpace", "nullValue", "emptyValue", "nanValue", "positiveInf",
+ *       "negativeInf", "dateFormat", "timestampFormat", "maxColumns", "maxCharsPerColumn",
+ *       "mode", "columnNameOfCorruptRecord", "multiLine"
+ *
+ * Detailed information of these CSV options can be found at:
+ * https://spark.apache.org/docs/latest/api/java/org/apache/spark/sql/DataFrameReader.html#csv-scala.collection.Seq-
+ *
+ * If the source Avro schema is provided through the {@link org.apache.hudi.utilities.schema.FilebasedSchemaProvider}
+ * using "hoodie.deltastreamer.schemaprovider.source.schema.file" config, the schema is
+ * passed to the CSV reader without inferring the schema from the CSV file.
+ */
+public class CsvDFSSource extends RowSource {
+  // CsvSource config prefix
+  public static final String CSV_SRC_CONFIG_PREFIX = "hoodie.deltastreamer.csv.";
+  // CSV-specific configurations to pass in from Hudi to Spark
+  public static final List<String> CSV_CONFIG_KEYS = Arrays.asList(
+      "sep", "encoding", "quote", "escape", "charToEscapeQuoteEscaping", "comment",
+      "header", "enforceSchema", "inferSchema", "samplingRatio", "ignoreLeadingWhiteSpace",
+      "ignoreTrailingWhiteSpace", "nullValue", "emptyValue", "nanValue", "positiveInf",
+      "negativeInf", "dateFormat", "timestampFormat", "maxColumns", "maxCharsPerColumn",
+      "mode", "columnNameOfCorruptRecord", "multiLine"
+  );
+
+  private final DFSPathSelector pathSelector;
+  private final StructType sourceSchema;
+
+  public CsvDFSSource(TypedProperties props,
+      JavaSparkContext sparkContext,
+      SparkSession sparkSession,
+      SchemaProvider schemaProvider) {
+    super(props, sparkContext, sparkSession, schemaProvider);
+    this.pathSelector = new DFSPathSelector(props, sparkContext.hadoopConfiguration());
+    if (overriddenSchemaProvider != null) {
+      sourceSchema = (StructType) SchemaConverters.toSqlType(overriddenSchemaProvider.getSourceSchema()).dataType();
 
 Review comment:
   Good point.  Done.

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