org.apache.hadoop.tools.rumen.package-info Maven / Gradle / Ivy
The newest version!
/*
* 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.
*/
/** Rumen is a data extraction and analysis tool built for
* Apache Hadoop. Rumen mines job history
* logs to extract meaningful data and stores it into an easily-parsed format.
*
* The default output format of Rumen is JSON.
* Rumen uses the Jackson library to
* create JSON objects.
*
*
* The following classes can be used to programmatically invoke Rumen:
*
* -
* {@link org.apache.hadoop.tools.rumen.JobConfigurationParser}
* A parser to parse and filter out interesting properties from job
* configuration.
*
*
* Sample code:
*
*
* // An example to parse and filter out job name
*
* String conf_filename = .. // assume the job configuration filename here
*
* // construct a list of interesting properties
* List<String> interestedProperties = new ArrayList<String>();
* interestedProperties.add("mapreduce.job.name");
*
* JobConfigurationParser jcp =
* new JobConfigurationParser(interestedProperties);
*
* InputStream in = new FileInputStream(conf_filename);
* Properties parsedProperties = jcp.parse(in);
*
*
* Some of the commonly used interesting properties are enumerated in
* {@link org.apache.hadoop.tools.rumen.JobConfPropertyNames}.
*
* Note:
* A single instance of {@link org.apache.hadoop.tools.rumen.JobConfigurationParser}
* can be used to parse multiple job configuration files.
*
*
* -
* {@link org.apache.hadoop.tools.rumen.JobHistoryParser}
* A parser that parses job history files. It is an interface and actual
* implementations are defined as Enum in
* {@link org.apache.hadoop.tools.rumen.JobHistoryParserFactory}. Note that
* {@link org.apache.hadoop.tools.rumen.RewindableInputStream}
* is a wrapper class around {@link java.io.InputStream} to make the input
* stream rewindable.
*
*
* Sample code:
*
*
* // An example to parse a current job history file i.e a job history
* // file for which the version is known
*
* String filename = .. // assume the job history filename here
*
* InputStream in = new FileInputStream(filename);
*
* HistoryEvent event = null;
*
* JobHistoryParser parser = new CurrentJHParser(in);
*
* event = parser.nextEvent();
* // process all the events
* while (event != null) {
* // ... process all event
* event = parser.nextEvent();
* }
*
* // close the parser and the underlying stream
* parser.close();
*
*
*
* {@link org.apache.hadoop.tools.rumen.JobHistoryParserFactory} provides a
* {@link org.apache.hadoop.tools.rumen.JobHistoryParserFactory#getParser(org.apache.hadoop.tools.rumen.RewindableInputStream)}
* API to get a parser for parsing the job history file. Note that this
* API can be used if the job history version is unknown.
* Sample code:
*
*
* // An example to parse a job history for which the version is not
* // known i.e using JobHistoryParserFactory.getParser()
*
* String filename = .. // assume the job history filename here
*
* InputStream in = new FileInputStream(filename);
* RewindableInputStream ris = new RewindableInputStream(in);
*
* // JobHistoryParserFactory will check and return a parser that can
* // parse the file
* JobHistoryParser parser = JobHistoryParserFactory.getParser(ris);
*
* // now use the parser to parse the events
* HistoryEvent event = parser.nextEvent();
* while (event != null) {
* // ... process the event
* event = parser.nextEvent();
* }
*
* parser.close();
*
*
* Note:
* Create one instance to parse a job history log and close it after use.
*
* -
* {@link org.apache.hadoop.tools.rumen.TopologyBuilder}
* Builds the cluster topology based on the job history events. Every
* job history file consists of events. Each event can be represented using
* {@link org.apache.hadoop.mapreduce.jobhistory.HistoryEvent}.
* These events can be passed to {@link org.apache.hadoop.tools.rumen.TopologyBuilder} using
* {@link org.apache.hadoop.tools.rumen.TopologyBuilder#process(org.apache.hadoop.mapreduce.jobhistory.HistoryEvent)}.
* A cluster topology can be represented using {@link org.apache.hadoop.tools.rumen.LoggedNetworkTopology}.
* Once all the job history events are processed, the cluster
* topology can be obtained using {@link org.apache.hadoop.tools.rumen.TopologyBuilder#build()}.
*
*
* Sample code:
*
*
* // Building topology for a job history file represented using
* // 'filename' and the corresponding configuration file represented
* // using 'conf_filename'
* String filename = .. // assume the job history filename here
* String conf_filename = .. // assume the job configuration filename here
*
* InputStream jobConfInputStream = new FileInputStream(filename);
* InputStream jobHistoryInputStream = new FileInputStream(conf_filename);
*
* TopologyBuilder tb = new TopologyBuilder();
*
* // construct a list of interesting properties
* List<String> interestingProperties = new ArrayList%lt;String>();
* // add the interesting properties here
* interestingProperties.add("mapreduce.job.name");
*
* JobConfigurationParser jcp =
* new JobConfigurationParser(interestingProperties);
*
* // parse the configuration file
* tb.process(jcp.parse(jobConfInputStream));
*
* // read the job history file and pass it to the
* // TopologyBuilder.
* JobHistoryParser parser = new CurrentJHParser(jobHistoryInputStream);
* HistoryEvent e;
*
* // read and process all the job history events
* while ((e = parser.nextEvent()) != null) {
* tb.process(e);
* }
*
* LoggedNetworkTopology topology = tb.build();
*
*
*
* -
* {@link org.apache.hadoop.tools.rumen.JobBuilder}
* Summarizes a job history file.
* {@link org.apache.hadoop.tools.rumen.JobHistoryUtils} provides
* {@link org.apache.hadoop.tools.rumen.JobHistoryUtils#extractJobID(String)}
* API for extracting job id from job history or job configuration files
* which can be used for instantiating {@link org.apache.hadoop.tools.rumen.JobBuilder}.
* {@link org.apache.hadoop.tools.rumen.JobBuilder} generates a
* {@link org.apache.hadoop.tools.rumen.LoggedJob} object via
* {@link org.apache.hadoop.tools.rumen.JobBuilder#build()}.
* See {@link org.apache.hadoop.tools.rumen.LoggedJob} for more details.
*
*
* Sample code:
*
*
* // An example to summarize a current job history file 'filename'
* // and the corresponding configuration file 'conf_filename'
*
* String filename = .. // assume the job history filename here
* String conf_filename = .. // assume the job configuration filename here
*
* InputStream jobConfInputStream = new FileInputStream(job_filename);
* InputStream jobHistoryInputStream = new FileInputStream(conf_filename);
*
* String jobID = TraceBuilder.extractJobID(job_filename);
* JobBuilder jb = new JobBuilder(jobID);
*
* // construct a list of interesting properties
* List<String> interestingProperties = new ArrayList%lt;String>();
* // add the interesting properties here
* interestingProperties.add("mapreduce.job.name");
*
* JobConfigurationParser jcp =
* new JobConfigurationParser(interestingProperties);
*
* // parse the configuration file
* jb.process(jcp.parse(jobConfInputStream));
*
* // parse the job history file
* JobHistoryParser parser = new CurrentJHParser(jobHistoryInputStream);
* try {
* HistoryEvent e;
* // read and process all the job history events
* while ((e = parser.nextEvent()) != null) {
* jobBuilder.process(e);
* }
* } finally {
* parser.close();
* }
*
* LoggedJob job = jb.build();
*
*
* Note:
* The order of parsing the job configuration file or job history file is
* not important. Create one instance to parse the history file and job
* configuration.
*
* -
* {@link org.apache.hadoop.tools.rumen.DefaultOutputter}
* Implements {@link org.apache.hadoop.tools.rumen.Outputter} and writes
* JSON object in text format to the output file.
* {@link org.apache.hadoop.tools.rumen.DefaultOutputter} can be
* initialized with the output filename.
*
*
* Sample code:
*
*
* // An example to summarize a current job history file represented by
* // 'filename' and the configuration filename represented using
* // 'conf_filename'. Also output the job summary to 'out.json' along
* // with the cluster topology to 'topology.json'.
*
* String filename = .. // assume the job history filename here
* String conf_filename = .. // assume the job configuration filename here
*
* Configuration conf = new Configuration();
* DefaultOutputter do = new DefaultOutputter();
* do.init("out.json", conf);
*
* InputStream jobConfInputStream = new FileInputStream(filename);
* InputStream jobHistoryInputStream = new FileInputStream(conf_filename);
*
* // extract the job-id from the filename
* String jobID = TraceBuilder.extractJobID(filename);
* JobBuilder jb = new JobBuilder(jobID);
* TopologyBuilder tb = new TopologyBuilder();
*
* // construct a list of interesting properties
* List<String> interestingProperties = new ArrayList%lt;String>();
* // add the interesting properties here
* interestingProperties.add("mapreduce.job.name");
*
* JobConfigurationParser jcp =
* new JobConfigurationParser(interestingProperties);
*
* // parse the configuration file
* tb.process(jcp.parse(jobConfInputStream));
*
* // read the job history file and pass it to the
* // TopologyBuilder.
* JobHistoryParser parser = new CurrentJHParser(jobHistoryInputStream);
* HistoryEvent e;
* while ((e = parser.nextEvent()) != null) {
* jb.process(e);
* tb.process(e);
* }
*
* LoggedJob j = jb.build();
*
* // serialize the job summary in json (text) format
* do.output(j);
*
* // close
* do.close();
*
* do.init("topology.json", conf);
*
* // get the job summary using TopologyBuilder
* LoggedNetworkTopology topology = topologyBuilder.build();
*
* // serialize the cluster topology in json (text) format
* do.output(topology);
*
* // close
* do.close();
*
*
*
* -
* {@link org.apache.hadoop.tools.rumen.JobTraceReader}
* A reader for reading {@link org.apache.hadoop.tools.rumen.LoggedJob} serialized using
* {@link org.apache.hadoop.tools.rumen.DefaultOutputter}. {@link org.apache.hadoop.tools.rumen.LoggedJob}
* provides various APIs for extracting job details. Following are the most
* commonly used ones
*
* - {@link org.apache.hadoop.tools.rumen.LoggedJob#getMapTasks()} : Get the map tasks
* - {@link org.apache.hadoop.tools.rumen.LoggedJob#getReduceTasks()} : Get the reduce tasks
* - {@link org.apache.hadoop.tools.rumen.LoggedJob#getOtherTasks()} : Get the setup/cleanup tasks
* - {@link org.apache.hadoop.tools.rumen.LoggedJob#getOutcome()} : Get the job's outcome
* - {@link org.apache.hadoop.tools.rumen.LoggedJob#getSubmitTime()} : Get the job's submit time
* - {@link org.apache.hadoop.tools.rumen.LoggedJob#getFinishTime()} : Get the job's finish time
*
*
*
* Sample code:
*
*
* // An example to read job summary from a trace file 'out.json'.
* JobTraceReader reader = new JobTracerReader("out.json");
* LoggedJob job = reader.getNext();
* while (job != null) {
* // .... process job level information
* for (LoggedTask task : job.getMapTasks()) {
* // process all the map tasks in the job
* for (LoggedTaskAttempt attempt : task.getAttempts()) {
* // process all the map task attempts in the job
* }
* }
*
* // get the next job
* job = reader.getNext();
* }
* reader.close();
*
*
*
* -
* {@link org.apache.hadoop.tools.rumen.ClusterTopologyReader}
* A reader to read {@link org.apache.hadoop.tools.rumen.LoggedNetworkTopology} serialized using
* {@link org.apache.hadoop.tools.rumen.DefaultOutputter}. {@link org.apache.hadoop.tools.rumen.ClusterTopologyReader} can be
* initialized using the serialized topology filename.
* {@link org.apache.hadoop.tools.rumen.ClusterTopologyReader#get()} can
* be used to get the
* {@link org.apache.hadoop.tools.rumen.LoggedNetworkTopology}.
*
*
* Sample code:
*
*
* // An example to read the cluster topology from a topology output file
* // 'topology.json'
* ClusterTopologyReader reader = new ClusterTopologyReader("topology.json");
* LoggedNetworkTopology topology = reader.get();
* for (LoggedNetworkTopology t : topology.getChildren()) {
* // process the cluster topology
* }
* reader.close();
*
*
*
*
*/
package org.apache.hadoop.tools.rumen;© 2015 - 2025 Weber Informatics LLC | Privacy Policy