Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/908
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dc.contributor.authorEstrada, Raúl-
dc.date.accessioned2026-07-09T07:29:00Z-
dc.date.available2026-07-09T07:29:00Z-
dc.date.issued2016-
dc.identifier.isbn978-1-78646-720-1-
dc.identifier.urihttp://hdl.handle.net/123456789/908-
dc.description.abstractThe 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.isoenen_US
dc.publisherPackt Publishingen_US
dc.relation.ispartofseries1151216;-
dc.subjectFast Data Processing Systems with SMACK Stacken_US
dc.titleFast Data Processing Systems with SMACK Stacken_US
dc.title.alternativeCombine 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.typeBooken_US
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