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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_r390761706
 
 

 ##########
 File path: hudi-utilities/src/test/java/org/apache/hudi/utilities/TestHoodieDeltaStreamer.java
 ##########
 @@ -693,6 +699,146 @@ public void testParquetDFSSourceWithSchemaFilesAndTransformer() throws
Exception
     testParquetDFSSource(true, TripsWithDistanceTransformer.class.getName());
   }
 
+  private void prepareCsvDFSSource(
+      boolean hasHeader, char sep, boolean useSchemaProvider, boolean hasTransformer) throws
IOException {
+    String sourceRoot = dfsBasePath + "/csvFiles";
+    String recordKeyField = (hasHeader || useSchemaProvider) ? "_row_key" : "_c0";
+
+    // Properties used for testing delta-streamer with CSV source
+    TypedProperties csvProps = new TypedProperties();
+    csvProps.setProperty("include", "base.properties");
+    csvProps.setProperty("hoodie.datasource.write.recordkey.field", recordKeyField);
+    csvProps.setProperty("hoodie.datasource.write.partitionpath.field", "not_there");
+    if (useSchemaProvider) {
+      csvProps.setProperty("hoodie.deltastreamer.schemaprovider.source.schema.file", dfsBasePath
+ "/source-flattened.avsc");
+      if (hasTransformer) {
+        csvProps.setProperty("hoodie.deltastreamer.schemaprovider.target.schema.file", dfsBasePath
+ "/target-flattened.avsc");
+      }
+    }
+    csvProps.setProperty("hoodie.deltastreamer.source.dfs.root", sourceRoot);
+
+    if (sep != ',') {
+      if (sep == '\t') {
+        csvProps.setProperty("hoodie.deltastreamer.csv.sep", "\\t");
+      } else {
+        csvProps.setProperty("hoodie.deltastreamer.csv.sep", Character.toString(sep));
+      }
+    }
+    if (hasHeader) {
+      csvProps.setProperty("hoodie.deltastreamer.csv.header", Boolean.toString(hasHeader));
+    }
+
+    UtilitiesTestBase.Helpers.savePropsToDFS(csvProps, dfs, dfsBasePath + "/" + PROPS_FILENAME_TEST_CSV);
+
+    String path = sourceRoot + "/1.csv";
+    HoodieTestDataGenerator dataGenerator = new HoodieTestDataGenerator();
+    UtilitiesTestBase.Helpers.saveCsvToDFS(
+        hasHeader, sep,
+        Helpers.jsonifyRecords(dataGenerator.generateInserts("000", CSV_NUM_RECORDS, true)),
+        dfs, path);
+  }
+
+  private void testCsvDFSSource(
+      boolean hasHeader, char sep, boolean useSchemaProvider, String transformerClassName)
throws Exception {
+    prepareCsvDFSSource(hasHeader, sep, useSchemaProvider, transformerClassName != null);
+    String tableBasePath = dfsBasePath + "/test_csv_table" + testNum;
+    String sourceOrderingField = (hasHeader || useSchemaProvider) ? "timestamp" : "_c0";
+    HoodieDeltaStreamer deltaStreamer =
+        new HoodieDeltaStreamer(TestHelpers.makeConfig(
+            tableBasePath, Operation.INSERT, CsvDFSSource.class.getName(),
+            transformerClassName, PROPS_FILENAME_TEST_CSV, false,
+            useSchemaProvider, 1000, false, null, null, sourceOrderingField), jsc);
+    deltaStreamer.sync();
+    TestHelpers.assertRecordCount(CSV_NUM_RECORDS, tableBasePath + "/*/*.parquet", sqlContext);
+    testNum++;
+  }
+
+  @Test
+  public void testCsvDFSSourceWithHeaderWithoutSchemaProviderAndNoTransformer() throws Exception
{
+    // The CSV files have header, the columns are separated by ',', the default separator
+    // No schema provider is specified, no transformer is applied
+    // In this case, the source schema comes from the inferred schema of the CSV files
+    testCsvDFSSource(true, ',', false, null);
+  }
+
+  @Test
+  public void testCsvDFSSourceWithHeaderAndSepWithoutSchemaProviderAndNoTransformer() throws
Exception {
+    // The CSV files have header, the columns are separated by '\t',
+    // which is passed in through the Hudi CSV properties
+    // No schema provider is specified, no transformer is applied
+    // In this case, the source schema comes from the inferred schema of the CSV files
+    testCsvDFSSource(true, '\t', false, null);
+  }
+
+  @Test
+  public void testCsvDFSSourceWithHeaderAndSepWithSchemaProviderAndNoTransformer() throws
Exception {
+    // The CSV files have header, the columns are separated by '\t'
+    // File schema provider is used, no transformer is applied
+    // In this case, the source schema comes from the source Avro schema file
+    testCsvDFSSource(true, '\t', true, null);
+  }
+
+  @Test
+  public void testCsvDFSSourceWithHeaderAndSepWithoutSchemaProviderAndWithTransformer() throws
Exception {
+    // The CSV files have header, the columns are separated by '\t'
+    // No schema provider is specified, transformer is applied
+    // In this case, the source schema comes from the inferred schema of the CSV files.
+    // Target schema is determined based on the Dataframe after transformation
+    testCsvDFSSource(true, '\t', false, TripsWithDistanceTransformer.class.getName());
+  }
+
+  @Test
+  public void testCsvDFSSourceWithHeaderAndSepWithSchemaProviderAndTransformer() throws Exception
{
+    // The CSV files have header, the columns are separated by '\t'
+    // File schema provider is used, transformer is applied
+    // In this case, the source and target schema come from the Avro schema files
+    testCsvDFSSource(true, '\t', true, TripsWithDistanceTransformer.class.getName());
+  }
+
+  @Test
+  public void testCsvDFSSourceNoHeaderWithoutSchemaProviderAndNoTransformer() throws Exception
{
+    // The CSV files do not have header, the columns are separated by '\t',
+    // which is passed in through the Hudi CSV properties
+    // No schema provider is specified, no transformer is applied
+    // In this case, the source schema comes from the inferred schema of the CSV files
+    // No CSV header and no schema provider at the same time are not recommended
 
 Review comment:
   The schema can still be inferred from the CSV source.  Although this might not be a common
use case, I don't want to rule this out, since Spark CSV data source supports schema inference.

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