Package com.hazelcast.jet.hadoop

Class HadoopSources

java.lang.Object
com.hazelcast.jet.hadoop.HadoopSources
public final class HadoopSources extends Object
Contains factory methods for Apache Hadoop sources.
Since:
Jet 3.0

  • Field Details

    • COPY_ON_READ

      public static final String COPY_ON_READ
      With the new HDFS API, some of the RecordReaders return the same key/value instances for each record, for example LineRecordReader. If this property is set to true, the source makes a copy of each object after applying the projectionFn. For readers which create a new instance for each record, the source can be configured to not copy the objects for performance.

      Also if you are using a projection function which doesn't refer to any mutable state from the key or value, then it makes sense to set this property to false to avoid unnecessary copying.

      The source copies the objects by serializing and de-serializing them. The objects should be either Writable or serializable in a way which Jet can serialize/de-serialize.

      Here is how you can configure the source. Default and always safe value is true: 

      
     Configuration conf = new Configuration();
     conf.setBoolean(HadoopSources.COPY_ON_READ, false);
     BatchSource<Entry<K, V>> source = HadoopSources.inputFormat(conf);
      See Also:

    • SHARED_LOCAL_FS

      public static final String SHARED_LOCAL_FS
      When reading files from local file system using Hadoop, each processor reads files from its own local file system. If the local file system is shared between members, e.g NFS mounted filesystem, you should configure this property as true.

      Here is how you can configure the source. Default value is false: 

      
     Configuration conf = new Configuration();
     conf.setBoolean(HadoopSources.SHARED_LOCAL_FS, true);
     BatchSource<Entry<K, V>> source = HadoopSources.inputFormat(conf);
      Since:
      Jet 4.4
      See Also:

    • IGNORE_FILE_NOT_FOUND

      public static final String IGNORE_FILE_NOT_FOUND
      Since:
      Jet 4.4
      See Also:

  • Method Details

    • inputFormat

      @Nonnull public static <K, V, E> BatchSource<E> inputFormat(@Nonnull org.apache.hadoop.conf.Configuration configuration, @Nonnull BiFunctionEx<K,V,E> projectionFn)
      Returns a source that reads records from Apache Hadoop HDFS and emits the results of transforming each record (a key-value pair) with the supplied projection function.

      This source splits and balances the input data among Jet processors, doing its best to achieve data locality. To this end the Jet cluster topology should be aligned with Hadoop's — on each Hadoop member there should be a Jet member.

      The processor will use either the new or the old MapReduce API based on the key which stores the InputFormat configuration. If it's stored under "mapreduce.job.inputformat.class", the new API will be used. Otherwise, the old API will be used. If you get the configuration from JobContextImpl.getConfiguration(), the new API will be used. Please see COPY_ON_READ if you are using the new API.

      The default local parallelism for this processor is 2 (or less if less CPUs are available).

      This source does not save any state to snapshot. If the job is restarted, all entries will be emitted again.

      Type Parameters:
      K - key type of the records
      V - value type of the records
      E - the type of the emitted value
      Parameters:
      configuration - JobConf for reading files with the appropriate input format and path
      projectionFn - function to create output objects from key and value. If the projection returns a null for an item, that item will be filtered out

    • inputFormat

      @Nonnull public static <K, V, E> BatchSource<E> inputFormat(@Nonnull ConsumerEx<org.apache.hadoop.conf.Configuration> configureFn, @Nonnull BiFunctionEx<K,V,E> projectionFn)
      Returns a source that reads records from Apache Hadoop HDFS and emits the results of transforming each record (a key-value pair) with the supplied projection function.

      This source splits and balances the input data among Jet processors, doing its best to achieve data locality. To this end the Jet cluster topology should be aligned with Hadoop's — on each Hadoop member there should be a Jet member.

      The configureFn is used to configure the MR Job. The function is run on the coordinator node of the Jet Job, avoiding contacting the server from the machine where the job is submitted.

      The new MapReduce API will be used.

      The default local parallelism for this processor is 2 (or less if less CPUs are available).

      This source does not save any state to snapshot. If the job is restarted, all entries will be emitted again.

      Type Parameters:
      K - key type of the records
      V - value type of the records
      E - the type of the emitted value
      Parameters:
      configureFn - function to configure the MR job
      projectionFn - function to create output objects from key and value. If the projection returns a null for an item, that item will be filtered out

    • inputFormat

      @Nonnull public static <K, V> BatchSource<Map.Entry<K,V>> inputFormat(@Nonnull org.apache.hadoop.conf.Configuration jobConf)
      Convenience for inputFormat(Configuration, BiFunctionEx) with Map.Entry as its output type.