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AWS Big Data Blog Interactive Analysis of Genomic Datasets Using Amazon Athena Aaron Friedman is a Healthcare and Life Sciences Solutions Architect with Amazon Web Services The genomics industry is in the midst of a data explosion. Due to the rapid drop in the cost to sequence genomes, genomics is now central to many medical advances. When your genome is sequenced and analyzed, raw sequencing file
AWS Big Data Blog Submitting User Applications with spark-submit Francisco Oliveira is a consultant with AWS Professional Services Customers starting their big data journey often ask for guidelines on how to submit user applications to Spark running on Amazon EMR. For example, customers ask for guidelines on how to size memory and compute resources available to their applications and the best reso
Facebook often uses analytics for data-driven decision making. Over the past few years, user and product growth has pushed our analytics engines to operate on data sets in the tens of terabytes for a single query. Some of our batch analytics is executed through the venerable Hive platform (contributed to Apache Hive by Facebook in 2009) and Corona, our custom MapReduce implementation. Facebook has
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AWS Big Data Blog Analyze Your Data on Amazon DynamoDB with Apache Spark Manjeet Chayel is a Solutions Architect with AWS Every day, tons of customer data is generated, such as website logs, gaming data, advertising data, and streaming videos. Many companies capture this information as itâs generated and process it in real time to understand their customers. Amazon DynamoDB is a fast and flexible
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SparkR (R on Spark) Overview SparkDataFrame Starting Up: SparkSession Starting Up from RStudio Creating SparkDataFrames From local data frames From Data Sources From Hive tables SparkDataFrame Operations Selecting rows, columns Grouping, Aggregation Operating on Columns Applying User-Defined Function Run a given function on a large dataset using dapply or dapplyCollect dapply dapplyCollect Run a g
AWS Week in Review â AWS Documentation Updates, Amazon EventBridge is Faster, and More â May 22, 2023 Here are your AWS updates from the previous 7 days. Last week I was in Turin, Italy for CloudConf, a conference Iâve had the pleasure to participate in for the last 10 years. AWS Hero Anahit Pogosova was also there sharing a few serverless tips in front of a full house. Hereâs a picture I [â¦] Amaz
ADAM is a library and command line tool that enables the use of Apache Spark to parallelize genomic data analysis across cluster/cloud computing environments. ADAM uses a set of schemas to describe genomic sequences, reads, variants/genotypes, and features, and can be used with data in legacy genomic file formats such as SAM/BAM/CRAM, BED/GFF3/GTF, and VCF, as well as data stored in the columnar A
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