Mastering Kafka streams and ksqIDB : (Record no. 80317)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01801nam a22001577a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 220824b2021 |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9788194722953 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 004.21 SEY-M |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Seymour, Mitch |
| 245 ## - TITLE STATEMENT | |
| Title | Mastering Kafka streams and ksqIDB : |
| Remainder of title | building real time data systems by example / |
| Statement of responsibility, etc. | Mitch Seymour |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc. | India |
| Name of publisher, distributor, etc. | Shroff Publishers |
| Date of publication, distribution, etc. | 2021 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 409 p. |
| 365 ## - TRADE PRICE | |
| Price type code | INR |
| Price amount | 1600.00. |
| 500 ## - GENERAL NOTE | |
| General note | Working 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.<br/><br/>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.<br/><br/>Learn the basics of Kafka and the pub/sub communication pattern<br/>Build stateless and stateful stream processing applications using Kafka Streams and ksqlDB<br/>Perform advanced stateful operations, including windowed joins and aggregations<br/>Understand how stateful processing works under the hood<br/>Learn about ksqlDB's data integration features, powered by Kafka Connect<br/>Work with different types of collections in ksqlDB and perform push and pull queries<br/>Deploy your Kafka Streams and ksqlDB applications to production. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Electronic data processing--Structured techniques |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| Withdrawn status | |
| Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Date last checked out | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | 003-007 | BITS Pilani Hyderabad | BITS Pilani Hyderabad | General Stack (For lending) | 24/08/2022 | 1 | 004.21 SEY-M | 46118 | 13/07/2024 | 20/04/2024 | 24/08/2022 | Books |