Java tutorial
/* * 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.parquet.hadoop; import org.apache.hadoop.conf.Configuration; import org.apache.parquet.Log; import org.apache.parquet.io.ParquetDecodingException; import org.apache.parquet.io.api.RecordMaterializer.RecordMaterializationException; // Essentially taken from: // https://github.com/twitter/elephant-bird/blob/master/core/src/main/java/com/twitter/elephantbird/mapreduce/input/LzoRecordReader.java#L124 /** * Tracks number of records that cannot be materialized and throws ParquetDecodingException * if the rate of errors crosses a limit.<p> These types of errors are meant * to be recoverable record conversion errors, such as a union missing a value, or schema * mismatch and so on. It's not meant to recover from corruptions in the parquet * columns themselves. * * The intention is to skip over very rare file corruption or bugs where * the write path has allowed invalid records into the file, but still catch large * numbers of failures. Not turned on by default (by default, no errors are tolerated). */ public class UnmaterializableRecordCounter { /* Tolerated percent bad records */ public static final String BAD_RECORD_THRESHOLD_CONF_KEY = "parquet.read.bad.record.threshold"; private static final Log LOG = Log.getLog(UnmaterializableRecordCounter.class); private static final float DEFAULT_THRESHOLD = 0f; private long numErrors; private final double errorThreshold; // max fraction of errors allowed private final long totalNumRecords; // how many records are we going to see total? public UnmaterializableRecordCounter(Configuration conf, long totalNumRecords) { this(conf.getFloat(BAD_RECORD_THRESHOLD_CONF_KEY, DEFAULT_THRESHOLD), totalNumRecords); } public UnmaterializableRecordCounter(double errorThreshold, long totalNumRecords) { this.errorThreshold = errorThreshold; this.totalNumRecords = totalNumRecords; numErrors = 0; } public void incErrors(RecordMaterializationException cause) throws ParquetDecodingException { numErrors++; LOG.warn(String.format("Error while reading an input record (%s out of %s): ", numErrors, totalNumRecords), cause); if (numErrors > 0 && errorThreshold <= 0) { // no errors are tolerated throw new ParquetDecodingException("Error while decoding records", cause); } double errRate = numErrors / (double) totalNumRecords; if (errRate > errorThreshold) { String message = String.format( "Decoding error rate of at least %s/%s crosses configured threshold of %s", numErrors, totalNumRecords, errorThreshold); LOG.error(message); throw new ParquetDecodingException(message, cause); } } }