Pipe Engineering.

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Presentation transcript:

Pipe Engineering

IdoFriedman.yml Name: Ido Friedman, Past:[SQL Server consultant, Instructor, Team Leader] Present: [Data engineer, Architect] Technologies: [Elasticsearch,CouchBase,MongoDB,Python,SQL …] WorkPlace: Perion WhenNotWorking: @Sea

Lambda Architecture Lambda architecture is a data-processing architecture designed to handle massive quantities of data by taking advantage of both batch- and stream-processing methods.

Lambda Example

Lambda Example

Data processing Batch Micro batch Streaming

Tools of the trade Processing Source/Targets HDFS SQL Server Amazon S3 MongoDB Azure EventHub ELK Stack Azure blob storage AWS Kinesis

All very nice BUT… Lots of systems = Lots of issues + Lots of data movements Lots of knowable required

ETL vs Streaming ETL Streaming Row by Row (not always) Shifting data window Supports many data structures in many cases Streaming Batch processing Known data window Known data structure Known and expected behavior patterns Small number of data platforms in one process

StreamSets http://www.streamsets.com Performance Management for Data Flows  Not an ETL tool Open Source Many connectors and integration Integration to Kafka / Hadoop at cluster mode No coding is required – But is fully supported VERY simple deployment http://www.streamsets.com

Piping Challenges Data Enrichment Windowing Performance Excepted results Data visibility Flexibility Scaling Monitoring

StreamSets SDC

SDC Cluster and Streaming mode SDC runs as an application within Spark Streaming SDC runs as an application on top of MapReduce

What are we doing with SDC Error and application Log analysis (ELK = SDC+K) Clickstream Ad Hoc needs

What are we connecting Amazon S3 JDBC Consumer ElasticSearch RabbitMQ AWS Kinesis SQL Server Amazon S3 JDBC Consumer ElasticSearch RabbitMQ File Tail Redis

Some numbers 100+M events per day including record level operations On a 2CPU 8GB machine (Centos 7)

Recommended reading` https://www.oreilly.com/ideas/the-world-beyond-batch-streaming-101 https://www.oreilly.com/ideas/the-world-beyond-batch-streaming-102