Communication-Efficient Cluster Scalable Genomics Data Processing Using Apache Arrow Flight

Author:

Ahmad Tanveer,Ma Chengxin,Al-Ars Zaid,Hofstee H. Peter

Abstract

Current cluster scaled genomics data processing solutions rely on big data frameworks like Apache Spark, Hadoop and HDFS for data scheduling, processing and storage. These frameworks come with additional computation and memory overheads by default. It has been observed that scaling genomics dataset processing beyond 32 nodes is not efficient on such frameworks.To overcome the inefficiencies of big data frameworks for processing genomics data on clusters, we introduce a low-overhead and highly scalable solution on a SLURM based HPC batch system. This solution uses Apache Arrow as in-memory columnar data format to store genomics data efficiently and Arrow Flight as a network protocol to move and schedule this data across the HPC nodes with low communication overhead.As a use case, we use NGS short reads DNA sequencing data for pre-processing and variant calling applications. This solution outperforms existing Apache Spark based big data solutions in term of both computation time (2x) and lower communication overhead (more than 20-60% depending on cluster size). Our solution has similar performance to MPI-based HPC solutions, with the added advantage of easy programmability and transparent big data scalability. The whole solution is Python and shell script based, which makes it flexible to update and integrate alternative variant callers. Our solution is publicly available on GitHub at https://github.com/abs-tudelft/time-to-fly-high/genomics.

Publisher

Cold Spring Harbor Laboratory

Reference20 articles.

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2. SparkBWA: Speeding Up the Alignment of High-Throughput DNA Sequencing Data;PLOS ONE 11,2016

3. Optimizing performance of GATK workflows using Apache Arrow In-Memory data framework;BMC Genomics 21,2020

4. T. Ahmad , N. Ahmed , J. Peltenburg , and Z. Al-Ars . 2020. ArrowSAM: In-Memory Genomics Data Processing Using Apache Arrow. In 2020 3rd International Conference on Computer Applications Information Security (ICCAIS). 1–6.

5. Apache. 2019. Apache Arrow: A cross-language development platform for in-memory data. Retrieved April 11, 2019 from https://arrow.apache.org/

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