KurtYoung commented on a change in pull request #10022: [FLINK-14135][orc] Introduce OrcColumnarRowInputFormat URL: https://github.com/apache/flink/pull/10022#discussion_r344024232
########## File path: flink-connectors/flink-connector-hive/src/main/java/org/apache/flink/connectors/hive/InputFormatUtil.java ########## @@ -0,0 +1,141 @@ +/* + * 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.flink.connectors.hive; + +import org.apache.flink.api.common.io.InputFormat; +import org.apache.flink.core.fs.Path; +import org.apache.flink.orc.OrcColumnarRowInputFormat; +import org.apache.flink.table.api.TableSchema; +import org.apache.flink.table.catalog.CatalogTable; +import org.apache.flink.table.dataformat.BaseRow; + +import org.apache.hadoop.conf.Configuration; +import org.apache.hadoop.hive.metastore.api.FieldSchema; +import org.apache.hadoop.hive.metastore.api.StorageDescriptor; +import org.apache.hadoop.hive.ql.io.orc.OrcInputFormat; +import org.apache.hadoop.hive.serde2.typeinfo.TypeInfoUtils; +import org.apache.hadoop.mapred.JobConf; +import org.apache.orc.TypeDescription; + +import java.util.Arrays; +import java.util.List; +import java.util.Map; +import java.util.stream.Collectors; + +/** + * Util to create hive input format. + */ +class InputFormatUtil { + + private static boolean useOrcVectorizedRead( + CatalogTable catalogTable, + List<HiveTablePartition> partitions, + int[] projectedFields) { + TableSchema schema = catalogTable.getSchema(); + boolean support = Arrays.stream(schema.getFieldDataTypes()).allMatch(t -> { + switch (t.getLogicalType().getTypeRoot()) { + case CHAR: + case VARCHAR: + case BOOLEAN: + case BINARY: + case VARBINARY: + case DECIMAL: + case TINYINT: + case SMALLINT: + case INTEGER: + case BIGINT: + case FLOAT: + case DOUBLE: + case DATE: + case TIME_WITHOUT_TIME_ZONE: + return true; + default: + return false; + } + }); + + boolean hasPartField = Arrays.stream(projectedFields).anyMatch(i -> + catalogTable.getPartitionKeys().contains( + catalogTable.getSchema().getFieldNames()[i])); + if (hasPartField) { + support = false; + } + + if (partitions.isEmpty()) { + support = false; + } + + String inputFormat = null; + Map<String, String> parameters = null; + for (HiveTablePartition partition : partitions) { + StorageDescriptor sd = partition.getStorageDescriptor(); + boolean isOrc = sd.getSerdeInfo().getSerializationLib().toLowerCase().contains("orc"); + if (!isOrc) { + support = false; + } + + if (inputFormat != null && !inputFormat.equals(sd.getInputFormat())) { + support = false; + } else { + inputFormat = sd.getInputFormat(); + } + + if (parameters != null && !parameters.equals(sd.getSerdeInfo().getParameters())) { + support = false; + } else { + parameters = sd.getSerdeInfo().getParameters(); + } + } + + return support; + } + + static InputFormat<BaseRow, ?> createInputFormat( + JobConf jobConf, + CatalogTable catalogTable, + List<HiveTablePartition> partitions, + int[] projectedFields) { + if (!useOrcVectorizedRead(catalogTable, partitions, projectedFields)) { Review comment: LOG this, to show whether we are using a vectorized reader, and the reason why we can't use vectorized version if happens. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services
