bowenli86 commented on a change in pull request #8700: [FLINK-12657][hive] Integrate Flink with Hive UDF URL: https://github.com/apache/flink/pull/8700#discussion_r293166188
########## File path: flink-connectors/flink-connector-hive/src/main/java/org/apache/flink/table/functions/hive/HiveSimpleUDF.java ########## @@ -0,0 +1,135 @@ +/* + * 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.table.functions.hive; + +import org.apache.flink.annotation.Internal; +import org.apache.flink.table.catalog.hive.util.HiveTypeUtil; +import org.apache.flink.table.functions.hive.conversion.HiveInspectors; +import org.apache.flink.table.functions.hive.conversion.HiveObjectConversion; +import org.apache.flink.table.functions.hive.conversion.IdentityConversion; +import org.apache.flink.table.types.DataType; + +import org.apache.hadoop.hive.ql.exec.FunctionRegistry; +import org.apache.hadoop.hive.ql.exec.UDF; +import org.apache.hadoop.hive.ql.exec.UDFArgumentException; +import org.apache.hadoop.hive.ql.metadata.HiveException; +import org.apache.hadoop.hive.ql.udf.generic.GenericUDFUtils; +import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector; +import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory; +import org.apache.hadoop.hive.serde2.typeinfo.TypeInfo; +import org.apache.hadoop.hive.serde2.typeinfo.TypeInfoUtils; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.lang.reflect.Method; +import java.util.ArrayList; +import java.util.Arrays; +import java.util.List; + +import static org.apache.flink.util.Preconditions.checkArgument; + +/** + * A ScalarFunction implementation that calls Hive's {@link UDF}. + */ +@Internal +public class HiveSimpleUDF extends HiveScalarFunction<UDF> { + + private static final Logger LOG = LoggerFactory.getLogger(HiveSimpleUDF.class); + + private transient Method method; + private transient GenericUDFUtils.ConversionHelper conversionHelper; + private transient HiveObjectConversion[] conversions; + private transient boolean allIdentityConverter; + + public HiveSimpleUDF(HiveFunctionWrapper<UDF> hiveFunctionWrapper) { + super(hiveFunctionWrapper); + LOG.info("Creating HiveSimpleUDF from '{}'", this.hiveFunctionWrapper.getClassName()); + } + + @Override + public void openInternal() { + LOG.info("Opening HiveSimpleUDF as '{}'", hiveFunctionWrapper.getClassName()); + + function = hiveFunctionWrapper.createFunction(); + + List<TypeInfo> typeInfos = new ArrayList<>(); + + for (DataType arg : argTypes) { + typeInfos.add(HiveTypeUtil.toHiveTypeInfo(arg)); + } + + try { + method = function.getResolver().getEvalMethod(typeInfos); + returnInspector = ObjectInspectorFactory.getReflectionObjectInspector(method.getGenericReturnType(), + ObjectInspectorFactory.ObjectInspectorOptions.JAVA); + ObjectInspector[] argInspectors = new ObjectInspector[typeInfos.size()]; + + for (int i = 0; i < argTypes.length; i++) { + argInspectors[i] = TypeInfoUtils.getStandardJavaObjectInspectorFromTypeInfo(typeInfos.get(i)); + } + + conversionHelper = new GenericUDFUtils.ConversionHelper(method, argInspectors); + conversions = new HiveObjectConversion[argInspectors.length]; + for (int i = 0; i < argInspectors.length; i++) { + conversions[i] = HiveInspectors.getConversion(argInspectors[i]); + } + + allIdentityConverter = Arrays.stream(conversions) + .allMatch(conv -> conv instanceof IdentityConversion); + } catch (Exception e) { + throw new FlinkHiveUDFException( + String.format("Failed to open HiveSimpleUDF from %s", hiveFunctionWrapper.getClassName()), e); + } + } + + @Override + public Object evalInternal(Object[] args) { + checkArgument(args.length == conversions.length); + + if (!allIdentityConverter) { Review comment: just by the logic itself, I think it can be faster for complex types and nested types, I don't have benchmarks and users' usage pattern. I don't think it's critically important, either removing or keeping it. This is more of referencing how we did it in Blink rather than intentionally trying to optimize it hard. If you feel really strong on removing it, we can surely do that ---------------------------------------------------------------- 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: us...@infra.apache.org With regards, Apache Git Services
