pyspark_sam
This repo hosts my code for the article "Analyze Big Sequence Alignments with PySpark in AWS EMR".
Prerequisite
-
Spark
-
AWS CLI
-
AWS Account
Run
Follow the instruction in the article. Once you have uploaded the files into your S3 bucket, run
aws emr create-cluster --name "Spark_step_pip" \
--release-label emr-6.5.0 \
--applications Name=Spark \
--log-uri s3://[your_S3_bucket]/logs/ \
--instance-type m5.xlarge \
--instance-count 3 \
--bootstrap-actions Path=s3://[your_S3_bucket]/emr_bootstrap.sh \
--use-default-roles --auto-terminate \
--steps "Type=Spark,Name=SparkProgram,ActionOnFailure=CONTINUE,Args=[--deploy-mode,cluster,--master,yarn,--py-files,s3://[your_S3_bucket]/helper_function.py,s3://[your_S3_bucket]/spark_3mer.py,s3://[your_S3_bucket]/test.sam,[your_S3_bucket],sankey.json]"
When the job finishes, download the sankey.json. And run this command to visualize:
python sankey.py sankey.json
Authors
- Sixing Huang - Concept and Coding
License
This project is licensed under the MIT License - see the LICENSE file for details
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