partitioner

How to properly apply HashPartitioner before a join in Spark?

由 假如想象 提交于 2020-06-26 13:53:28
问题 To reduce shuffling during the joining of two RDDs, I decided to partition them using HashPartitioner first. Here is how I do it. Am I doing it correctly, or is there a better way to do this? val rddA = ... val rddB = ... val numOfPartitions = rddA.getNumPartitions val rddApartitioned = rddA.partitionBy(new HashPartitioner(numOfPartitions)) val rddBpartitioned = rddB.partitionBy(new HashPartitioner(numOfPartitions)) val rddAB = rddApartitioned.join(rddBpartitioned) 回答1: To reduce shuffling

How to properly apply HashPartitioner before a join in Spark?

由 ぃ、小莉子 提交于 2020-06-26 13:53:16
问题 To reduce shuffling during the joining of two RDDs, I decided to partition them using HashPartitioner first. Here is how I do it. Am I doing it correctly, or is there a better way to do this? val rddA = ... val rddB = ... val numOfPartitions = rddA.getNumPartitions val rddApartitioned = rddA.partitionBy(new HashPartitioner(numOfPartitions)) val rddBpartitioned = rddB.partitionBy(new HashPartitioner(numOfPartitions)) val rddAB = rddApartitioned.join(rddBpartitioned) 回答1: To reduce shuffling

How outputcollector works?

由 自古美人都是妖i 提交于 2019-12-25 05:19:14
问题 I was trying to analyse the default map reduce job, that doesn't define a mapper or a reducer. i.e. one that uses IdentityMapper & IdentityReducer To make myself clear I just wrote my identity reducer public static class MyIdentityReducer extends MapReduceBase implements Reducer<Text,Text,Text,Text> { @Override public void reduce(Text key, Iterator<Text> values, OutputCollector<Text, Text> output, Reporter reporter) throws IOException { while(values.hasNext()) { Text value = values.next();

Why does sortBy transformation trigger a Spark job?

由 不打扰是莪最后的温柔 提交于 2019-12-17 09:55:46
问题 As per Spark documentation only RDD actions can trigger a Spark job and the transformations are lazily evaluated when an action is called on it. I see the sortBy transformation function is applied immediately and it is shown as a job trigger in the SparkUI. Why? 回答1: sortBy is implemented using sortByKey which depends on a RangePartitioner (JVM) or partitioning function (Python). When you call sortBy / sortByKey partitioner (partitioning function) is initialized eagerly and samples input RDD

Hash value from keys on Cassandra

由 ╄→гoц情女王★ 提交于 2019-12-13 04:33:59
问题 I'm developing a mechanism for Cassandra using Hector. What I need at this moment is to know which are the hash values of the keys to look at which node is stored (looking at the tokens of each one), and ask directly this node for the value. What I understood is that depending on the partitioner Cassandra uses, the values are stored independently from one partitioner to other. So, are the hash values of all keys stored in any table? In case not, how could I implement a generic class that once

Hadoop partitioner

由 我的未来我决定 提交于 2019-12-05 01:34:12
问题 I want to ask about Hadoop partitioner ,is it implemented within Mappers?. How to measure the performance of using the default hash partitioner - Is there better partitioner to reducing data skew? Thanks 回答1: Partitioner is not within Mapper. Below is the process that happens in each Mapper - Each map task writes its output to a circular buffer memory (and not to disk). When the buffer reaches a threshold, a background thread starts to spill the contents to disk. [Buffer size is governed by

how to sort word count by value in hadoop? [duplicate]

由 杀马特。学长 韩版系。学妹 提交于 2019-11-30 17:44:23
This question already has an answer here: hadoop map reduce secondary sorting 5 answers hi i wanted to learn how to sort the word count by value in hadoop.i know hadoop takes of sorting keys, but not by values. i know to sort the values we must have a partitioner,groupingcomparator and a sortcomparator but i am bit confused in applying these concepts together to sort the word count by value. do we need another map reduce job to achieve the same or else a combiner to count the occurrences and then sort here and emit the same to reducer? can any one explain how to sort word count example by

how to sort word count by value in hadoop? [duplicate]

由 北慕城南 提交于 2019-11-30 01:50:33
问题 This question already has answers here : hadoop map reduce secondary sorting (5 answers) Closed 6 years ago . hi i wanted to learn how to sort the word count by value in hadoop.i know hadoop takes of sorting keys, but not by values. i know to sort the values we must have a partitioner,groupingcomparator and a sortcomparator but i am bit confused in applying these concepts together to sort the word count by value. do we need another map reduce job to achieve the same or else a combiner to
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