RussellSpitzer commented on a change in pull request #3132: URL: https://github.com/apache/iceberg/pull/3132#discussion_r715174045
########## File path: spark/src/main/java/org/apache/iceberg/spark/SparkReadConf.java ########## @@ -0,0 +1,192 @@ +/* + * 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.iceberg.spark; + +import java.util.Map; +import java.util.Set; +import org.apache.iceberg.FileFormat; +import org.apache.iceberg.Table; +import org.apache.iceberg.TableProperties; +import org.apache.iceberg.hadoop.HadoopInputFile; +import org.apache.iceberg.io.InputFile; +import org.apache.iceberg.relocated.com.google.common.collect.ImmutableSet; +import org.apache.iceberg.util.PropertyUtil; +import org.apache.spark.sql.RuntimeConfig; +import org.apache.spark.sql.SparkSession; + +/** + * A class for common Iceberg configs for Spark reads. + * <p> + * If a config is set at multiple levels, the following order of precedence is used (top to bottom): + * <ol> + * <li>Read options</li> + * <li>Session configuration</li> + * <li>Table metadata</li> + * </ol> + * The most specific value is set in read options and takes precedence over all other configs. + * If no read option is provided, this class checks the session configuration for any overrides. + * If no applicable value is found in the session configuration, this classes uses the table metadata. + * <p> + * Note this class is NOT meant to be serialized and sent to executors. + */ +public class SparkReadConf { + + private static final Set<String> LOCALITY_WHITELIST_FS = ImmutableSet.of("hdfs"); + + private final Table table; + private final RuntimeConfig sessionConf; + private final Map<String, String> readOptions; + + public SparkReadConf(SparkSession spark, Table table, Map<String, String> readOptions) { + this.table = table; + this.sessionConf = spark.conf(); + this.readOptions = readOptions; + } + + public boolean localityEnabled() { + InputFile file = table.io().newInputFile(table.location()); + + if (file instanceof HadoopInputFile) { + String scheme = ((HadoopInputFile) file).getFileSystem().getScheme(); + boolean defaultValue = LOCALITY_WHITELIST_FS.contains(scheme); + return PropertyUtil.propertyAsBoolean( + readOptions, + SparkReadOptions.LOCALITY, + defaultValue); + } + + return false; + } + + public boolean vectorizationEnabled(FileFormat fileFormat) { + String readOptionValue = readOptions.get(SparkReadOptions.VECTORIZATION_ENABLED); + if (readOptionValue != null) { + return Boolean.parseBoolean(readOptionValue); + } + + String sessionConfValue = sessionConf.get(SparkSQLConfigs.VECTORIZATION_ENABLED, null); + if (sessionConfValue != null) { + return Boolean.parseBoolean(sessionConfValue); + } + + switch (fileFormat) { + case PARQUET: + return PropertyUtil.propertyAsBoolean( + table.properties(), + TableProperties.PARQUET_VECTORIZATION_ENABLED, + TableProperties.PARQUET_VECTORIZATION_ENABLED_DEFAULT); + + case ORC: + return PropertyUtil.propertyAsBoolean( + table.properties(), + TableProperties.ORC_VECTORIZATION_ENABLED, + TableProperties.ORC_VECTORIZATION_ENABLED_DEFAULT); + + default: + return false; + } + } + + public int batchSize(FileFormat fileFormat) { + String readOptionValue = readOptions.get(SparkReadOptions.VECTORIZATION_BATCH_SIZE); + if (readOptionValue != null) { + return Integer.parseInt(readOptionValue); + } + + switch (fileFormat) { + case PARQUET: + return PropertyUtil.propertyAsInt( + table.properties(), + TableProperties.PARQUET_BATCH_SIZE, + TableProperties.PARQUET_BATCH_SIZE_DEFAULT); + + case ORC: + return PropertyUtil.propertyAsInt( + table.properties(), + TableProperties.ORC_BATCH_SIZE, + TableProperties.ORC_BATCH_SIZE_DEFAULT); + + default: + throw new IllegalArgumentException("File format does not support batch reads: " + fileFormat); + } + } + + public long splitSize() { + String readOptionValue = readOptions.get(SparkReadOptions.SPLIT_SIZE); Review comment: Seems like we use this pattern a lot, may make sense to have a getConfiguredLong(String name, Long default) getConfiguredLong(SparkReadOptions.SPLIT_SIZE, TableProperties.SPLIT_SIZE_DEFAULT) OI wish our "propertyAsX" was parameterized then I would say just have getConfigured[X](String name, X default) : X -- This is an automated message from the Apache Git Service. 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