Apache Spark : Reading and Writing Sequence Files

Writing a Sequence file:

scala> val data = sc.parallelize(List(("key1", 1), ("Kay2", 2), ("Key3", 2)))
data: org.apache.spark.rdd.RDD[(String, Int)] = ParallelCollectionRDD[7] at parallelize at :27
scala> data.saveAsSequenceFile("/tmp/seq-output")

The output can be verified using hadoop ls command

[root@maprdemo sample-data]# hadoop fs -lsr /tmp/seq-output
lsr: DEPRECATED: Please use 'ls -R' instead.
-rwxr-xr-x   1 root root          0 2015-10-02 01:12 /tmp/seq-output/_SUCCESS
-rw-r--r--   1 root root        102 2015-10-02 01:12 /tmp/seq-output/part-00000
-rw-r--r--   1 root root        119 2015-10-02 01:12 /tmp/seq-output/part-00001
[root@maprdemo sample-data]# hadoop fs -text /tmp/seq-output/part-00001
Kay2 2
Key3 2

Reading Sequence file

scala> import org.apache.hadoop.io.Text
import org.apache.hadoop.io.Text
scala> import org.apache.hadoop.io.IntWritable
import org.apache.hadoop.io.IntWritable
val result = sc.sequenceFile("/tmp/seq-output/part-00001", classOf[Text], classOf[IntWritable]). map{case (x, y) => (x.toString, y.get())}
scala> val result = sc.sequenceFile("/tmp/seq-output/part-00001", classOf[Text], classOf[IntWritable]). map{case (x, y) => (x.toString, y.get())}
result: org.apache.spark.rdd.RDD[(String, Int)] = MapPartitionsRDD[15] at map at :29

scala> result.collect
res14: Array[(String, Int)] = Array((Kay2,2), (Key3,2))

Hadoop : Merging Small tar files to the Sequence File

The Hadoop Distributed File System (HDFS) is a distributed file system. It is mainly designed for batch processing of large volume of data. The default block size of HDFS is 64MB. When data is represented in files significantly smaller than the default block size the performance degrades dramatically. Mainly there are two reasons for producing small files. One reason is some files are pieces of a larger logical file (e.g. - log files). Since HDFS has only recently supported appends, these unbounded files are saved by writing them in chunks into HDFS. Other reason is some files cannot be combined together into one larger file and are essentially small. e.g. - A large corpus of images where each image is a distinct file.

Solution to the small files by merging them into a Sequence File:

Sequence files is a Hadoop specific archive file format similar to tar and zip. The concept behind this is to merge the file set with using a key and a value pair and this created files known as ‘Hadoop Sequence Files’. In this method file name is used as the key and the file content is used as value.

In the proposed solution we will demonstrate how to write small files to the Sequence File and a Sequence file reader which will list the file name in Sequence File:

Setting up a local file system:

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;

public class LocalSetup {

    private FileSystem fileSystem;
    private Configuration config;

    
    public LocalSetup() throws Exception {
        config = new Configuration();

        
        config.set("fs.file.impl", "org.apache.hadoop.fs.LocalFileSystem");

        fileSystem = FileSystem.get(config);
        if (fileSystem.getConf() == null) {
                throw new Exception("LocalFileSystem configuration is null");
        }
    }

    
    public Configuration getConf() {
        return config;
    }

    
    public FileSystem getLocalFileSystem() {
        return fileSystem;
    }
}

In the next course of action we will setup a class which will read from the .tar.gz,.tgz,.tar.bz2 extension files and write it to the Sequence File with key as the name of file and value be the content of the file:

import org.apache.tools.bzip2.CBZip2InputStream;
import org.apache.tools.tar.TarEntry;
import org.apache.tools.tar.TarInputStream;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.LocalFileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.SequenceFile;
import org.apache.hadoop.io.Text;

import java.io.File;
import java.io.FileInputStream;
import java.io.InputStream;
import java.io.IOException;
import java.util.zip.GZIPInputStream;



public class TarToSeqFile {

    private File inputFile;
    private File outputFile;
    private LocalSetup setup;

    
    public TarToSeqFile() throws Exception {
        setup = new LocalSetup();
    }

    
    public void setInput(File inputFile) {
        this.inputFile = inputFile;
    }

    public void setOutput(File outputFile) {
        this.outputFile = outputFile;
    }

    public void execute() throws Exception {
        TarInputStream input = null;
        SequenceFile.Writer output = null;
        try {
            input = openInputFile();
            output = openOutputFile();
            TarEntry entry;
            while ((entry = input.getNextEntry()) != null) {
                if (entry.isDirectory()) { continue; }
                String filename = entry.getName();
                byte[] data = TarToSeqFile.getBytes(input, entry.getSize());
                
                Text key = new Text(filename);
                BytesWritable value = new BytesWritable(data);
                output.append(key, value);
            }
        } finally {
            if (input != null) { input.close(); }
            if (output != null) { output.close(); }
        }
    }

    private TarInputStream openInputFile() throws Exception {
        InputStream fileStream = new FileInputStream(inputFile);
        String name = inputFile.getName();
        InputStream theStream = null;
        if (name.endsWith(".tar.gz") || name.endsWith(".tgz")) {
            theStream = new GZIPInputStream(fileStream);
        } else if (name.endsWith(".tar.bz2") || name.endsWith(".tbz2")) {
            fileStream.skip(2);
            theStream = new CBZip2InputStream(fileStream);
        } else {
            theStream = fileStream;
        }
        return new TarInputStream(theStream);
    }

    private SequenceFile.Writer openOutputFile() throws Exception {
        Path outputPath = new Path(outputFile.getAbsolutePath());
        return SequenceFile.createWriter(setup.getLocalFileSystem(), setup.getConf(),
                                         outputPath,
                                         Text.class, BytesWritable.class,
                                         SequenceFile.CompressionType.BLOCK);
    }

    
    private static byte[] getBytes(TarInputStream input, long size) throws Exception {
        if (size > Integer.MAX_VALUE) {
            throw new Exception("A file in the tar archive is too large.");
        }
        int length = (int)size;
        byte[] bytes = new byte[length];

        int offset = 0;
        int numRead = 0;

        while (offset < bytes.length &&
               (numRead = input.read(bytes, offset, bytes.length - offset)) >= 0) {
            offset += numRead;
        }

        if (offset < bytes.length) {
            throw new IOException("A file in the tar archive could not be completely read.");
        }

        return bytes;
    }

    
    public static void main(String[] args) {
        if (args.length != 2) {
            exitWithHelp();
        }

        try {
            TarToSeqFile me = new TarToSeqFile();
            me.setInput(new File(args[0]));
            me.setOutput(new File(args[1]));
            me.execute();
        } catch (Exception e) {
            e.printStackTrace();
            exitWithHelp();
        }
    }

    public static void exitWithHelp() {
        System.err.println("Usage:  <tarfile> TarToSeqFile  <output>\n\n" +
                           "<tarfile> may be GZIP or BZIP2 compressed, must have a\n" +
                           "recognizable extension .tar, .tar.gz, .tgz, .tar.bz2, or .tbz2.");
        System.exit(1);
    }
}

In this way we can write files to a single Sequence file, to test it further we will read from the Sequence file and list the keys of the file as output

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.LocalFileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.SequenceFile;
import org.apache.hadoop.io.Writable;


public class SeqKeyList {

    private String inputFile;
    private LocalSetup setup;

    public SeqKeyList() throws Exception {
        setup = new LocalSetup();
    }

    public void setInput(String filename) {
        inputFile = filename;
    }

    
    public void execute() throws Exception {
        Path path = new Path(inputFile);
        SequenceFile.Reader reader = 
            new SequenceFile.Reader(setup.getLocalFileSystem(), path, setup.getConf());

        try {
            System.err.println("Key type is " + reader.getKeyClassName());
            System.err.println("Value type is " + reader.getValueClassName());
            if (reader.isCompressed()) {
                System.err.println("Values are compressed.");
            }
            if (reader.isBlockCompressed()) {
                System.err.println("Records are block-compressed.");
            }
            System.err.println("Compression type is " + reader.getCompressionCodec().getClass().getName());
            System.err.println("");

            Writable key = (Writable)(reader.getKeyClass().newInstance());
            while (reader.next(key)) {
                System.out.println(key.toString());
            }
        } finally {
            reader.close();
        }
    }

    public static void main(String[] args) {
        if (args.length != 1) {
            exitWithHelp();
        }

        try {
            SeqKeyList me = new SeqKeyList();
            me.setInput(args[0]);
            me.execute();
        } catch (Exception e) {
            e.printStackTrace();
            exitWithHelp();
        }
    }

    
    public static void exitWithHelp() {
        System.err.println("Usage: SeqKeyList   <sequence-file>\n" +
                           "Prints a list of keys in the sequence file, one per line.");
        System.exit(1);
    }
}

Hadoop : How to read and write Sequence File using mapreduce

Sequence files is a Hadoop specific archive file format similar to tar and zip. The concept behind this is to merge the file set with using a key and a value pair and this created files known as ‘Hadoop Sequence Files’. In this method file name is used as the key and the file content is used as value.

A sequence file consists of a header followed by one or more records. The first three bytes of a sequence file are the bytes SEQ, which acts a magic number, followed by a single byte representing the version number. The header contains other fields including the names of the key and value classes, compression details, user-defined metadata, and the sync marker. Recall that the sync marker is used to allow a reader to synchronize to a record boundary from any position in the file. Each file has a randomly generated sync marker, whose value is stored in the header. Sync markers appear between records in the sequence file. They are designed to incur less than a 1% storage overhead, so they don’t necessarily appear between every pair of records (such is the case for short records).



The internal format of the records depends on whether compression is enabled, and if it is, whether it is record compression or block compression.

If no compression is enabled (the default), then each record is made up of the record length (in bytes), the key length, the key, and then the value. The length fields are written as four-byte integers adhering to the contract of the writeInt() method of java.io.DataOutput. Keys and values are serialized using the Serialization defined for the class being written to the sequence file.

In this sample code I will demonstarate you how to read and write the sequence file. The Complete code is available on my Git repo

we will use the the following sample data:

#custId orderNo
965412 S986512
965413 S986513
965414 S986514
965415 S986515
965416 S986516

configure the hadoop related dependencies in the pom.xml

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
  <modelVersion>4.0.0</modelVersion>
  <groupId>com.rjkrsinghhadoop</groupId>
  <artifactId>SequenceFileReaderWriter</artifactId>
  <packaging>jar</packaging>
  <version>1.0-SNAPSHOT</version>
  <name>SequenceFileReaderWriter</name>
  <url>http://maven.apache.org</url>
  <dependencies>
        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit</artifactId>
            <version>4.7</version>
            <scope>test</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-core</artifactId>
            <version>1.0.4</version>
        </dependency>
        <dependency>
            <groupId>commons-logging</groupId>
            <artifactId>commons-logging-api</artifactId>
            <version>1.0.4</version>
        </dependency>
        <dependency>
            <groupId>commons-logging</groupId>
            <artifactId>commons-logging</artifactId>
            <version>1.0.4</version>
            <scope>compile</scope>
        </dependency>
        <dependency>
            <groupId>commons-cli</groupId>
            <artifactId>commons-cli</artifactId>
            <version>1.2</version>
        </dependency>
    </dependencies>

<!--
    <repositories>
        <repository>
            <id>libdir</id>
            <url>file://${basedir}/lib</url>
        </repository>
    </repositories>
-->

    <build>
        <finalName>exploringhadoop</finalName>
        <plugins>
   <plugin>
    <groupId>org.apache.maven.plugins</groupId>
    <artifactId>maven-compiler-plugin</artifactId>
    <configuration>
     <source>1.6</source>
     <target>1.6</target>
    </configuration>
   </plugin>
   <plugin>
    <artifactId>maven-assembly-plugin</artifactId>
    <configuration>
     <finalName>${project.name}-${project.version}</finalName>
     <appendAssemblyId>true</appendAssemblyId>
     <descriptors>
      <descriptor>src/main/assembly/assembly.xml</descriptor>
     </descriptors>
    </configuration>
   </plugin>
        </plugins>
    </build>
</project>

Now create a mapper class to as follows:

package com.rjkrsinghhadoop;

import java.io.IOException;

import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

public class SequenceFileWriterMapper extends Mapper<Text,Text,Text,Text> {
        
        
        @Override
        protected void map(Text key, Text value,Context context)         throws IOException, InterruptedException {
                context.write(key, value);                
        }

}

Create a java class SequenceFileWriterApp which will write a text file to the Sequence file

package com.rjkrsinghhadoop;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.KeyValueTextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat;

public class SequenceFileWriterApp 
{
    public static void main( String[] args ) throws Exception
    {
            if(args.length !=2 ){
                    System.err.println("Usage : Sequence File Writer Utility <input path> <output path>");
                    System.exit(-1);
            }
            Configuration conf = new Configuration();
            Job job = new Job(conf);
            job.setJarByClass(SequenceFileWriterApp.class);
            job.setJobName("SequenceFileWriter");
            
            FileInputFormat.addInputPath(job,new Path(args[0]) );
            FileOutputFormat.setOutputPath(job, new Path(args[1]));
            
            job.setMapperClass(SequenceFileWriterMapper.class);
            
            job.setInputFormatClass(KeyValueTextInputFormat.class);
            job.setOutputFormatClass(SequenceFileOutputFormat.class);
            
            job.setOutputKeyClass(Text.class);
            job.setOutputValueClass(Text.class);
            job.setNumReduceTasks(0);
            
            
            System.exit(job.waitForCompletion(true) ? 0:1);
    }
}

To read a sequence file and convert it back to the txt file we need a SequenceFileReader

package com.rjkrsinghhadoop;

import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.KeyValueTextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class SequenceFileReader  {


  public static void main(String[] args) throws Exception {
          if(args.length !=2 ){
                System.err.println("Usage : Sequence File Writer Utility <input path> <output path>");
                System.exit(-1);
        }
        Configuration conf = new Configuration();
        Job job = new Job(conf);
        job.setJarByClass(SequenceFileReader.class);
        job.setJobName("SequenceFileReader");
        
        FileInputFormat.addInputPath(job,new Path(args[0]) );
        FileOutputFormat.setOutputPath(job, new Path(args[1]));
        
        job.setMapperClass(SequenceFileWriterMapper.class);
        
        job.setInputFormatClass(SequenceFileInputFormat.class);
        job.setOutputFormatClass(TextOutputFormat.class);
        
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);
        job.setNumReduceTasks(0);
        
        
        System.exit(job.waitForCompletion(true) ? 0:1);
}
}

r

ship your code in the jar file we will need an assembly descriptor create a assembly.xml in the resources folder as follows:

<assembly
    xmlns="http://maven.apache.org/plugins/maven-assembly-plugin/assembly/1.1.0"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xsi:schemaLocation="http://maven.apache.org/plugins/maven-assembly-plugin/assembly/1.1.0 http://maven.apache.org/xsd/assembly-1.1.0.xsd">
    <id>job</id>
    <formats>
        <format>jar</format>
    </formats>
    <includeBaseDirectory>false</includeBaseDirectory>
    <dependencySets>
        <dependencySet>
            <unpack>false</unpack>
            <scope>runtime</scope>
            <outputDirectory>lib</outputDirectory>
            <excludes>
                <exclude>${artifact.groupId}:${artifact.artifactId}</exclude>
            </excludes>
        </dependencySet>
        <dependencySet>
            <unpack>false</unpack>
            <scope>system</scope>
            <outputDirectory>lib</outputDirectory>
            <excludes>
                <exclude>${artifact.groupId}:${artifact.artifactId}</exclude>
            </excludes>
        </dependencySet>
    </dependencySets>
    <fileSets>
        <fileSet>
            <directory>${basedir}/target/classes</directory>
            <outputDirectory>/</outputDirectory>
            <excludes>
                <exclude>*.jar</exclude>
            </excludes>
        </fileSet>
    </fileSets>
</assembly>

now run mvn assembly:assembly which will create a jar file in the target directory, which is ready to be run on your hadoop cluster.