Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/908Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Estrada, Raúl | - |
| dc.date.accessioned | 2026-07-09T07:29:00Z | - |
| dc.date.available | 2026-07-09T07:29:00Z | - |
| dc.date.issued | 2016 | - |
| dc.identifier.isbn | 978-1-78646-720-1 | - |
| dc.identifier.uri | http://hdl.handle.net/123456789/908 | - |
| dc.description.abstract | The SMACK stack is a generalized web-scale data pipeline. It was popularized in the San Francisco Bay Area data engineering meet ups and conferences and spread around the world. SMACK stands for: S = Spark: This involves data in-memory distributed computing. Think in Apache Flink, Apache Ignite, Google Millwheel, and so on. M = Mesos: This involves Cluster OS, distributed system management, scheduling and scaling. Think in Apache YARN, Kubernetes, Docker, and so on. A = Akka: This is the API. It is an implementation of the actor's model. Think in Scala, Erlang, Elixir, GoLang and so on. C = Cassandra: This is a persistence layer, noSQL database. Think in Apache HBase, Riak, Google BigTable, MongoDB, and so on. K = Kafka: This is a distributed streaming platform, the message broker. Think in Apache Storm, ActiveMQ, RabbitMQ, Kestrel, JMS, and so on. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Packt Publishing | en_US |
| dc.relation.ispartofseries | 1151216; | - |
| dc.subject | Fast Data Processing Systems with SMACK Stack | en_US |
| dc.title | Fast Data Processing Systems with SMACK Stack | en_US |
| dc.title.alternative | Combine the incredible powers of Spark, Mesos, Akka, Cassandra, and Kafka to build data processing platforms that can take on even the hardest of your data troubles! | en_US |
| dc.type | Book | en_US |
| Appears in Collections: | E-Books | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Fast Data Processing Systems with SMACK.pdf | 7.73 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
