pinterest coordinates analysis ner_people ner_locations ner_dates ner_organizations cluster_id cluster_label class social_importance lda_vectors lda_topics F. HFile Generation Here, we show our MapReduce program to generate HFiles for the bulk-loading process (See Section 7.4.2). The mappers (for tweet and web pages) convert the input file (Avro) to a sequence of HBase operations. A reducer that comes with the HBase distribution handles “Put” these objects, but that part is opaque to the programmer. The programmer simply calls the “Put” right reducer using this statement: HFileOutputFormat.configureIncrementalLoad(job, htable); package cs5604.hadoop; import java.io.IOException; import org.apache.hadoop.hbase.HBaseConfiguration; import org.apache.hadoop.hbase.client.HTable; import org.apache.hadoop.hbase.client.Put; import org.apache.hadoop.hbase.io.ImmutableBytesWritable; import org.apache.hadoop.hbase.mapreduce.HFileOutputFormat; import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil; import org.apache.hadoop.hbase.util.Bytes; import org.apache.avro.Schema; org.apache.avro.mapred.AvroKey; import import org.apache.avro.mapreduce.AvroJob; import org.apache.avro.mapreduce.AvroKeyInputFormat; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.conf.Configured; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.NullWritable; import org.apache.hadoop.mapreduce.Job; org.apache.hadoop.mapreduce.Mapper; import import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
pinterest coordinates analysis ner_people ner_locations ner_dates ner_organizations cluster_id cluster_label class social_importance lda_vectors lda_topics F. HFile Generation Here, we show our MapReduce program to generate HFiles for the bulk-loading process (See Section 7.4.2). The mappers (for tweet and web pages) convert the input file (Avro) to a sequence of “Put” HBase operations. A reducer that comes with the HBase distribution handles these “Put” objects, but that part is opaque to the programmer. The programmer simply calls the right reducer using this statement: HFileOutputFormat.configureIncrementalLoad(job, htable); package cs5604.hadoop; import java.io.IOException; import org.apache.hadoop.hbase.HBaseConfiguration; import org.apache.hadoop.hbase.client.HTable; import org.apache.hadoop.hbase.client.Put; import org.apache.hadoop.hbase.io.ImmutableBytesWritable; import org.apache.hadoop.hbase.mapreduce.HFileOutputFormat; import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil; import org.apache.hadoop.hbase.util.Bytes; import org.apache.avro.Schema; import org.apache.avro.mapred.AvroKey; import org.apache.avro.mapreduce.AvroJob; import org.apache.avro.mapreduce.AvroKeyInputFormat; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.conf.Configured; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.NullWritable; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.Mapper; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
HadoopFinalReport.docx