Advanced EMR usage

Spot Instances

You can potentially save money purchasing EC2 instances for your EMR clusters from AWS’s spot market. The catch is that if someone bids more for instances that you’re using, they can be taken away from your cluster. If this happens, you aren’t charged, but your job may fail.

You can specify spot market bid prices using the core_instance_bid_price, master_instance_bid_price, and task_instance_bid_price options to specify a price in US dollars. For example, on the command line:

--task-instance-bid-price 0.42

or in mrjob.conf:

    task_instance_bid_price: '0.42'

(Note the quotes; bid prices are strings, not floats!)

Amazon has a pretty thorough explanation of why and when you’d want to use spot instances here. The brief summary is that either you don’t care if your job fails, in which case you want to purchase all your instances on the spot market, or you’d need your job to finish but you’d like to save time and money if you can, in which case you want to run task instances on the spot market and purchase master and core instances the regular way.

Cluster Pooling interacts with bid prices more or less how you’d expect; a job will join a pool with spot instances only if it requested spot instances at the same price or lower.

Bootstrap-time configuration

Some Hadoop options, such as the maximum number of running map tasks per node, must be set at bootstrap time and will not work with –jobconf. You must use Amazon’s configure-hadoop script for this. For example, this limits the number of mappers and reducers to one per node:

--bootstrap-action="s3://elasticmapreduce/bootstrap-actions/configure-hadoop \
-m \
-m mapred.tasktracker.reduce.tasks.maximum=1"


This doesn’t work on AMI 4.0.0 and later.

Manually Reusing Clusters

In some cases, it may be useful to have more fine-grained control than Cluster Pooling provides; for example, to run several related jobs on the same cluster.

mrjob includes a utility to create persistent clusters without running a job. For example, this command will create a cluster with 12 EC2 instances (1 master and 11 core), taking all other options from mrjob.conf:

$ mrjob create-cluster --num-core-instances=11

You can then add jobs to the cluster with the --cluster-id switch or the cluster_id option in mrjob.conf (see EMRJobRunner.__init__()):

$ python -r emr --cluster-id=j-CLUSTERID input_file.txt > out
Adding our job to existing cluster j-CLUSTERID

Debugging will be difficult unless you complete SSH setup (see Configuring SSH credentials) since the logs will not be copied from the master node to S3 before either five minutes pass or the cluster terminates.