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From GitBox <...@apache.org>
Subject [GitHub] [drill] arina-ielchiieva commented on a change in pull request #1951: DRILL-7454: Convert Avro to EVF
Date Mon, 06 Jan 2020 13:48:55 GMT
arina-ielchiieva commented on a change in pull request #1951: DRILL-7454: Convert Avro to EVF
URL: https://github.com/apache/drill/pull/1951#discussion_r363299653
 
 

 ##########
 File path: exec/java-exec/src/main/java/org/apache/drill/exec/store/avro/AvroBatchReader.java
 ##########
 @@ -0,0 +1,368 @@
+/*
+ * 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.drill.exec.store.avro;
+
+import org.apache.avro.Schema;
+import org.apache.avro.file.DataFileReader;
+import org.apache.avro.generic.GenericArray;
+import org.apache.avro.generic.GenericContainer;
+import org.apache.avro.generic.GenericDatumReader;
+import org.apache.avro.generic.GenericFixed;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.mapred.FsInput;
+import org.apache.avro.util.Utf8;
+import org.apache.drill.common.exceptions.UserException;
+import org.apache.drill.exec.physical.impl.scan.file.FileScanFramework;
+import org.apache.drill.exec.physical.impl.scan.framework.ManagedReader;
+import org.apache.drill.exec.physical.resultSet.ResultSetLoader;
+import org.apache.drill.exec.physical.resultSet.RowSetLoader;
+import org.apache.drill.exec.record.metadata.ColumnMetadata;
+import org.apache.drill.exec.record.metadata.TupleMetadata;
+import org.apache.drill.exec.util.ImpersonationUtil;
+import org.apache.drill.exec.vector.accessor.ArrayWriter;
+import org.apache.drill.exec.vector.accessor.DictWriter;
+import org.apache.drill.exec.vector.accessor.ObjectWriter;
+import org.apache.drill.exec.vector.accessor.ScalarWriter;
+import org.apache.drill.exec.vector.accessor.TupleWriter;
+import org.apache.drill.shaded.guava.com.google.common.base.Charsets;
+import org.apache.hadoop.fs.FileSystem;
+import org.apache.hadoop.fs.Path;
+import org.apache.hadoop.mapred.FileSplit;
+import org.apache.hadoop.security.UserGroupInformation;
+import org.joda.time.DateTimeConstants;
+import org.joda.time.Period;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.io.IOException;
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.nio.ByteBuffer;
+import java.nio.ByteOrder;
+import java.nio.IntBuffer;
+import java.security.PrivilegedExceptionAction;
+import java.util.List;
+import java.util.Map;
+
+public class AvroBatchReader implements ManagedReader<FileScanFramework.FileSchemaNegotiator>
{
+
+  private static final Logger logger = LoggerFactory.getLogger(AvroBatchReader.class);
+
+  // currently config is unused but maybe used later
+  private final AvroReaderConfig config;
+
+  private Path filePath;
+  private long endPosition;
+  private DataFileReader<GenericContainer> reader;
+  private ResultSetLoader loader;
+  // re-use container instance
+  private GenericContainer container = null;
+
+  public AvroBatchReader(AvroReaderConfig config) {
+    this.config = config;
+  }
+
+  @Override
+  public boolean open(FileScanFramework.FileSchemaNegotiator negotiator) {
+    FileSplit split = negotiator.split();
+    filePath = split.getPath();
+
+    // Avro files are splittable, define reading start / end positions
+    long startPosition = split.getStart();
+    endPosition = startPosition + split.getLength();
+
+    logger.debug("Processing Avro file: {}, start position: {}, end position: {}",
+      filePath, startPosition, endPosition);
+
+    reader = prepareReader(split, negotiator.fileSystem(),
+      negotiator.userName(), negotiator.context().getFragmentContext().getQueryUserName());
+
+    logger.debug("Avro file schema: {}", reader.getSchema());
+    TupleMetadata schema = AvroSchemaUtil.convert(reader.getSchema());
+    logger.debug("Avro file converted schema: {}", schema);
+    negotiator.setTableSchema(schema, true);
+    loader = negotiator.build();
+
+    return true;
+  }
+
+  @Override
+  public boolean next() {
+    RowSetLoader rowWriter = loader.writer();
+    while (!rowWriter.isFull()) {
+      if (!nextLine(rowWriter)) {
+        return false;
+      }
+    }
+    return true;
+  }
+
+  @Override
+  public void close() {
+    try {
+      reader.close();
+    } catch (IOException e) {
+      logger.warn("Error closing Avro reader: {}", e.getMessage(), e);
+    } finally {
+      reader = null;
+    }
+  }
+
+  @Override
+  public String toString() {
+    long currentPosition = -1L;
+    try {
+      if (reader != null) {
+        currentPosition = reader.tell();
+      }
+    } catch (IOException e) {
+      logger.trace("Unable to obtain Avro reader position: {}", e.getMessage(), e);
+    }
+    return "AvroBatchReader[File=" + filePath
+      + ", Position=" + currentPosition
+      + "]";
+  }
+
+  /**
+   * Initialized Avro data reader based on given file system and file path.
+   * Moves reader to the sync point from where to start reading the data.
+   *
+   * @param fileSplit file split
+   * @param fs file system
+   * @param opUserName name of the user whom to impersonate while reading the data
+   * @param queryUserName name of the user who issues the query
+   * @return Avro file reader
+   */
+  private DataFileReader<GenericContainer> prepareReader(FileSplit fileSplit, FileSystem
fs, String opUserName, String queryUserName) {
+    try {
+      UserGroupInformation ugi = ImpersonationUtil.createProxyUgi(opUserName, queryUserName);
+      DataFileReader<GenericContainer> reader = ugi.doAs((PrivilegedExceptionAction<DataFileReader<GenericContainer>>)
() ->
+        new DataFileReader<>(new FsInput(fileSplit.getPath(), fs.getConf()), new GenericDatumReader<GenericContainer>()));
+
+      // move to sync point from where to read the file
+      reader.sync(fileSplit.getStart());
+      return reader;
+    } catch (IOException | InterruptedException e) {
+      throw UserException.dataReadError(e)
+        .message("Error preparing Avro reader")
+        .addContext("Reader", this)
+        .build(logger);
+    }
+  }
+
+  private boolean nextLine(RowSetLoader rowWriter) {
+    try {
+      if (!reader.hasNext() || reader.pastSync(endPosition)) {
+        return false;
+      }
+      container = reader.next(container);
+    } catch (IOException e) {
+      throw UserException.dataReadError(e)
+        .addContext("Reader", this)
+        .build(logger);
+    }
+
+    Schema schema = container.getSchema();
+    GenericRecord record = (GenericRecord) container;
+
+    if (Schema.Type.RECORD != schema.getType()) {
+      throw UserException.dataReadError()
+        .message("Root object must be record type. Found: %s", schema.getType())
+        .addContext("Reader", this)
+        .build(logger);
+    }
+
+    rowWriter.start();
+    List<Schema.Field> fields = schema.getFields();
+    for (Schema.Field field : fields) {
+      String fieldName = field.name();
+      Object value = record.get(fieldName);
+      ObjectWriter writer = rowWriter.column(fieldName);
+      processRecord(writer, value, field.schema());
+    }
+    rowWriter.save();
+    return true;
+  }
+
+  private void processRecord(ObjectWriter writer, Object value, Schema schema) {
+    // skip processing record if it is null or is not projected
+    if (value == null || !writer.isProjected()) {
+      return;
+    }
+
+    switch (schema.getType()) {
+      case UNION:
+        processRecord(writer, value, AvroSchemaUtil.extractSchemaFromNullable(schema, writer.schema().name()));
+        break;
+      case RECORD:
+        TupleWriter tupleWriter = writer.tuple();
+
+        if (tupleWriter.tupleSchema().isEmpty()) {
+          // fill in tuple schema for cases when there recursive named record types are present
+          TupleMetadata recordSchema = AvroSchemaUtil.convert(schema);
+          recordSchema.toMetadataList().forEach(tupleWriter::addColumn);
+        }
+
+        GenericRecord genericRecord = (GenericRecord) value;
+        schema.getFields().forEach(
+          field -> processRecord(tupleWriter.column(field.name()), genericRecord.get(field.name()),
field.schema())
+        );
+        break;
+      case ARRAY:
+        ArrayWriter arrayWriter = writer.array();
+        GenericArray<?> array = (GenericArray<?>) value;
+        ObjectWriter entryWriter = arrayWriter.entry();
+        for (Object arrayValue : array) {
+          processRecord(entryWriter, arrayValue, array.getSchema().getElementType());
+          arrayWriter.save();
+        }
+        break;
+      case MAP:
+        @SuppressWarnings("unchecked")
+        Map<Object, Object> map = (Map<Object, Object>) value;
+        Schema valueSchema = schema.getValueType();
+
+        DictWriter dictWriter = writer.dict();
+        ScalarWriter keyWriter = dictWriter.keyWriter();
+        ObjectWriter valueWriter = dictWriter.valueWriter();
+
+        for (Map.Entry<Object, Object> mapEntry : map.entrySet()) {
+          processScalar(keyWriter, mapEntry.getKey());
+          processRecord(valueWriter, mapEntry.getValue(), valueSchema);
+          dictWriter.save();
+        }
+        break;
+      default:
+        try {
+          ScalarWriter scalarWriter = writer.scalar();
+          processScalar(scalarWriter, value);
+        } catch (UnsupportedOperationException e) {
+          throw UserException.dataReadError(e)
+            .message("Unexpected writer type '%s', expected scalar", writer.type())
+            .addContext("Reader", this)
+            .build(logger);
+        }
+    }
+  }
+
+  private void processScalar(ScalarWriter scalarWriter, Object value) {
+    ColumnMetadata columnMetadata = scalarWriter.schema();
+    switch (columnMetadata.type()) {
+      case INT:
+        scalarWriter.setInt((int) value);
+        break;
+      case BIGINT:
+        scalarWriter.setLong((long) value);
 
 Review comment:
   Well, most of the scalar type still have their own logic so left those that can be replaces
with setObject with casts for visibility. Having some casts implicitly, others not might be
a little confusing.

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