How do you set the number of mappers and reducers in hive?
How do you set the number of mappers and reducers in hive?
from my_hbase_table select col1, count(1) group by col1; The map reduce job spawns only 2 mappers and I’d like to increase that. With a plain map reduce job I would configure the yarn and mapper memory to increase the number of mappers.
How do you set the number of mappers in Hive query?
In order to manually set the number of mappers in a Hive query when TEZ is the execution engine, the configuration `tez. grouping. split-count` can be used by either:
- Setting it when logged into the HIVE CLI. In other words, `set tez. grouping.
- An entry in the `hive-site. xml` can be added through Ambari.
How do you set the number of reducers in hive?
4 Answers
- use this command to set desired number of reducers: set mapred.reduce.tasks=50.
- rewrite query as following:
How do I limit the number of mappers in hive?
- You can set the split minsize and maxsize to control the number of mappers.
- For e.g.
- If the file size is 300000 bytes, setting the following values will create 3 mappers.
- set mapreduce.input.fileinputformat.split.maxsize=100000;
- set mapreduce.input.fileinputformat.split.minsize=100000;
Does all 3 replicas of a block executed in parallel?
By any case, not more than one replica of the data block will be stored in the same machine. Every replica of the data block will be kept in different machines. The master node(jobtracker) may or may not pick the original data, in fact it doesn’t maintain any info about out of the 3 replica which is original.
Can we set number of mappers?
You cannot set number of mappers explicitly to a certain number which is less than the number of mappers calculated by Hadoop. This is decided by the number of Input Splits created by hadoop for your given set of input. You may control this by setting mapred.
How do you control the number of mappers?
How do you calculate the number of mappers and reducers?
of Mappers per MapReduce job:The number of mappers depends on the amount of InputSplit generated by trong>InputFormat (getInputSplits method). If you have 640MB file and Data Block size is 128 MB then we need to run 5 Mappers per MapReduce job. Reducers: There are two conditions for no.
How do you set the number of reducers?
The number of reducers can be set in two ways as below: Using the command line: While running the MapReduce job, we have an option to set the number of reducers which can be specified by the controller mapred. reduce. tasks.
How number of reducers are calculated?
1) Number of reducers is same as number of partitions. 2) Number of reducers is 0.95 or 1.75 multiplied by (no. of nodes) * (no. of maximum containers per node).
How do you set mappers and reducers in Hadoop jobs?
So, in order to control the Number of Mappers, you have to first control the Number of Input Splits Hadoop creates before running your MapReduce program. One of the easiest ways to control it is setting the property ‘mapred. max. split.
Why is HDFS block size 128MB?
The default size of a block in HDFS is 128 MB (Hadoop 2. x) which is much larger as compared to the Linux system where the block size is 4KB. The reason of having this huge block size is to minimize the cost of seek and reduce the meta data information generated per block.
Is it possible to know how many mappers and reducers hive query is?
Number of Mappers depends on the number of input splits calculated by the job client. And hive query is like series of Map reduce jobs. If you write a simple query like select Count (*) from company only one Map reduce Program will be executed.
How to limit number of Reduce tasks in hive?
You can modify using set mapred.map.tasks = b. mapred.reduce.tasks – The default number of reduce tasks per job is 1. Typically set to 99% of the cluster’s reduce capacity, so that if a node fails the reduces can still be executed in a single wave.
When to use combinehiveinputformat for hive mapper?
In a typical InputFormat, it is directly proportional to the number of files and file sizes. but suppose if you have 2 files with 30MB size (each file) then each file will occupy one block and mapper will get assigend based on that. When you are working with a large number of small files, Hive uses CombineHiveInputFormat by default.
How to increase the number of mappers in a cluster?
Also number of mappers and reducers are always dependent of available mapper and reducer slots of your cluster. Reduce the input split size from the default value. The mappers will get increased. Splitting the HBase table should get your job to use more mappers automatically.