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Posted to commits@doris.apache.org by GitBox <gi...@apache.org> on 2020/04/15 03:32:59 UTC
[GitHub] [incubator-doris] yangzhg commented on a change in pull request
#3296: spark data preparation process, issue #3295
yangzhg commented on a change in pull request #3296: spark data preparation process, issue #3295
URL: https://github.com/apache/incubator-doris/pull/3296#discussion_r408560620
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File path: fe/src/main/java/org/apache/doris/load/loadv2/dpp/DppUtils.java
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@@ -0,0 +1,230 @@
+// 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.doris.load.loadv2.dpp;
+
+import org.apache.doris.common.UserException;
+import org.apache.doris.load.loadv2.etl.EtlJobConfig;
+
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DataTypes;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+import org.apache.spark.sql.Row;
+
+import com.google.common.collect.Lists;
+
+import java.math.BigInteger;
+import java.nio.ByteBuffer;
+import java.nio.ByteOrder;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.Date;
+import java.util.List;
+import java.util.zip.CRC32;
+
+public class DppUtils {
+ public static final String BUCKET_ID = "__bucketId__";
+ public static Class dataTypeToClass(DataType dataType) {
+ if (dataType == null) {
+ return null;
+ }
+ if (dataType.equals(DataTypes.BooleanType)) {
+ return Boolean.class;
+ } else if (dataType.equals(DataTypes.ShortType)) {
+ return Short.class;
+ } else if (dataType.equals(DataTypes.IntegerType)) {
+ return Integer.class;
+ } else if (dataType.equals(DataTypes.LongType)) {
+ return Long.class;
+ } else if (dataType.equals(DataTypes.FloatType)) {
+ return Float.class;
+ } else if (dataType.equals(DataTypes.DoubleType)) {
+ return Double.class;
+ } else if (dataType.equals(DataTypes.DateType)) {
+ return Date.class;
+ } else if (dataType.equals(DataTypes.StringType)) {
+ return String.class;
+ }
+ return null;
+ }
+
+ public static Class columnTypeToClass(String columnType) {
+ switch (columnType) {
+ case "BOOL":
+ return Boolean.class;
+ case "TINYINT":
+ case "SMALLINT":
+ return Short.class;
+ case "INT":
+ return Integer.class;
+ case "DATETIME":
+ case "BIGINT":
+ return Long.class;
+ case "LARGEINT":
+ return BigInteger.class;
+ case "FLOAT":
+ return Float.class;
+ case "DOUBLE":
+ return Double.class;
+ case "DATE":
+ return Date.class;
+ case "HLL":
+ case "CHAR":
+ case "VARCHAR":
+ case "BITMAP":
+ case "OBJECT":
+ return String.class;
+ default:
+ return String.class;
+ }
+ }
+
+ public static DataType columnTypeToDataType(String columnType) throws UserException {
+ DataType dataType = DataTypes.StringType;
+ switch (columnType) {
+ case "BOOL":
+ dataType = DataTypes.BooleanType;
+ break;
+ case "TINYINT":
+ case "SMALLINT":
+ dataType = DataTypes.ShortType;
+ break;
+ case "INT":
+ dataType = DataTypes.IntegerType;
+ break;
+ case "DATETIME":
+ case "BIGINT":
+ case "LARGEINT":
+ // todo: special treat LARGEINT because spark do not support int128
+ dataType = DataTypes.LongType;
+ break;
+ case "FLOAT":
+ dataType = DataTypes.FloatType;
+ break;
+ case "DOUBLE":
+ dataType = DataTypes.DoubleType;
+ break;
+ case "DATE":
+ dataType = DataTypes.DateType;
+ break;
+ case "HLL":
+ case "CHAR":
+ case "VARCHAR":
+ case "BITMAP":
+ case "OBJECT":
+ dataType = DataTypes.StringType;
+ break;
+ default:
+ throw new UserException("Reason: invalid column type:" + columnType);
+ }
+ return dataType;
+ }
+
+ public static ByteBuffer getHashValue(Object o, DataType type) {
+ ByteBuffer buffer = ByteBuffer.allocate(8);
+ buffer.order(ByteOrder.LITTLE_ENDIAN);
+ if (o == null) {
+ buffer.putInt(0);
+ return buffer;
+ }
+ if (type.equals(DataTypes.ShortType)) {
+ buffer.putShort((Short)o);
+ } else if (type.equals(DataTypes.IntegerType)) {
+ buffer.putInt((Integer) o);
+ } else if (type.equals(DataTypes.LongType)) {
+ buffer.putLong((Long)o);
+ } else if (type.equals(DataTypes.StringType)) {
+ try {
+ String str = (String)o;
+ buffer = ByteBuffer.wrap(str.getBytes("UTF-8"));
+ } catch (Exception e) {
+ throw new RuntimeException(e);
+ }
+ }
+ return buffer;
+ }
+
+ public static long getHashValue(Row row, List<String> distributeColumns, StructType dstTableSchema) {
+ CRC32 hashValue = new CRC32();
+ for (String distColumn : distributeColumns) {
+ Object columnObject = row.get(row.fieldIndex(distColumn));
+ ByteBuffer buffer = getHashValue(columnObject, dstTableSchema.apply(distColumn).dataType());
+ hashValue.update(buffer.array(), 0, buffer.limit());
+ }
+ return hashValue.getValue();
+ }
+
+ public static StructType createDstTableSchema(List<EtlJobConfig.EtlColumn> columns, boolean addBucketIdColumn) throws UserException {
+ List<StructField> fields = new ArrayList<>();
+ if (addBucketIdColumn) {
+ StructField bucketIdField = DataTypes.createStructField(BUCKET_ID, DataTypes.StringType, true);
+ fields.add(bucketIdField);
+ }
+ for (EtlJobConfig.EtlColumn column : columns) {
+ String columnName = column.columnName;
+ String columnType = column.columnType;
Review comment:
seems not necessary to define columnName and columnType
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