Hadoop how many reducers

There is no fixed number of reducers task that can be configured or calculated. It depends on the moment how much of the resources are actually available to allocate. Number of reducer is internally calculated from size of the data we are processing if you don't explicitly specify using below API in driver program. You can change the configuration as well that instead of 1 GB you can specify the bigger size or smaller size. Your job may or may not need reducers, it depends on what are you trying to do.

When there are multiple reducers, the map tasks partition their output, each creating one partition for each reduce task. There can be many keys and their associated values in each partition, but the records for any given key are all in a single partition. Too many reducers and you end up with lots of small files. Partitioner makes sure that same keys from multiple mappers goes to the same reducer. This doesn't mean that number of partitions is equal to number of reducers.

However, you can specify number of reduce tasks in the driver program using job instance like job. If you don't specify the number of reduce tasks in the driver program then it picks from the mapred. Also, note that programmer will not have control over number of mappers as it depends on the input split where as programmer can control the number of reducers for any job. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams?

Collectives on Stack Overflow. Learn more. Number of reducers in hadoop Ask Question. Asked 5 years, 4 months ago. Active 4 years, 1 month ago. Viewed 18k times. I was learning hadoop, I found number of reducers very confusing : 1 Number of reducers is same as number of partitions. How is number of reducers is calculated?

Please tell me how to calculate number of reducers. Improve this question. Community Bot 1 1 1 silver badge. Use this if your specific use case permits.

Mapper generating more data as comped to input means , it is emitting more records as received , which means key duplication is happening Generally speaking. This is mostly used in all framework like Pig , as well as generally Reducer heap is in order of 1. This is a default number. Please tune according to your needs. Always good to underestimate while doing calculations for performance.

Can i handle it using partitioner? Do we have any other way? There are Many ways , best is to have a look at your skewed key and come to logical conclusion 1.

Look at Pig Skewed Join implementation add salt to your key and then reduce twice , divide and conquer 2. Take top N events for a given key If logic permits. Thanks for your suggestions and will try to incorporate your suggestions and come back to you with more questions! Support Questions. Find answers, ask questions, and share your expertise. Turn on suggestions. Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type. Showing results for. Search instead for.

Let us discuss the few differences between Here what happens is, each file would You can reference the below steps: Step Let us consider a student database table Firstly you need to understand the concept In your case there is no difference In Hdfs, data and metadata are decoupled. Open spark-shell.

Already have an account? Sign in. If there are two joins in hive how many mapreduce jobs will run. If there are two joins in hive, how many mapreduce jobs will run? Your comment on this question: Your name to display optional : Email me at this address if a comment is added after mine: Email me if a comment is added after mine Privacy: Your email address will only be used for sending these notifications.