000 01801nam a22001577a 4500
008 220824b2021 |||||||| |||| 00| 0 eng d
020 _a9788194722953
082 _a004.21 SEY-M
100 _aSeymour, Mitch
245 _aMastering Kafka streams and ksqIDB :
_bbuilding real time data systems by example /
_cMitch Seymour
260 _aIndia
_bShroff Publishers
_c2021
300 _a409 p.
365 _aINR
_b1600.00.
500 _aWorking with unbounded and fast-moving data streams has historically been difficult. But with Kafka Streams and ksqlDB, building stream processing applications is easy and fun. This practical guide shows data engineers how to use these tools to build highly scalable stream processing applications for moving, enriching, and transforming large amounts of data in real time. Mitch Seymour, data services engineer at Mailchimp, explains important stream processing concepts against a backdrop of several interesting business problems. You'll learn the strengths of both Kafka Streams and ksqlDB to help you choose the best tool for each unique stream processing project. Non-Java developers will find the ksqlDB path to be an especially gentle introduction to stream processing. Learn the basics of Kafka and the pub/sub communication pattern Build stateless and stateful stream processing applications using Kafka Streams and ksqlDB Perform advanced stateful operations, including windowed joins and aggregations Understand how stateful processing works under the hood Learn about ksqlDB's data integration features, powered by Kafka Connect Work with different types of collections in ksqlDB and perform push and pull queries Deploy your Kafka Streams and ksqlDB applications to production.
650 _aElectronic data processing--Structured techniques
999 _c80317
_d80317