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/*
 * 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
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package org.apache.parquet.hadoop;


import org.apache.hadoop.conf.Configuration;
import org.apache.parquet.ParquetReadOptions;
import org.apache.parquet.io.ParquetDecodingException;
import org.apache.parquet.io.api.RecordMaterializer.RecordMaterializationException;
import com.facebook.presto.hive.$internal.org.slf4j.Logger;
import com.facebook.presto.hive.$internal.org.slf4j.LoggerFactory;
import java.util.Map;

// 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.

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 Logger LOG = LoggerFactory.getLogger(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(ParquetReadOptions options, long totalNumRecords) { this(getFloat(options, 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); } } private static float getFloat(ParquetReadOptions options, String key, float defaultValue) { String value = options.getProperty(key); if (value != null) { return Float.valueOf(value); } else { return defaultValue; } } }





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