Building Better Distributed Data Pipelines
Patrick McFadin explains the basics of how to build more efficient data pipelines, using Apache Kafka to organize, Apache Cassandra to store, and Apache Spark to analyze. Patrick offers an overview of how Cassandra works and why it can be a perfect fit for data-driven projects. Patrick then demonstr...
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| Idioma: | Inglés |
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O'Reilly Media, Inc
2017.
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| Edición: | 1st edition |
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| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009631273706719 |
| Sumario: | Patrick McFadin explains the basics of how to build more efficient data pipelines, using Apache Kafka to organize, Apache Cassandra to store, and Apache Spark to analyze. Patrick offers an overview of how Cassandra works and why it can be a perfect fit for data-driven projects. Patrick then demonstrates that with the addition of Spark and Kafka, you can maintain a highly distributed, fault-tolerant, and scaling solution. You’ll leave with a comprehensive view of the many options to make considered choices in your data pipeline projects. |
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| Notas: | Title from resource description page (viewed December 19, 2017). |
| Descripción Física: | 1 online resource (1 video file, approximately 54 min.) |
