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Learn Apache Presto, Basic Apache Presto, Apache Presto book, Apache Presto concepts, Apache Presto app, Presto components, Apache Presto notes, Presto course, Presto tutorial.
Presto’s architecture is very similar to a classic database management system using cluster computing. It can be visualized as one coordinator node working in sync with multiple worker nodes. Clients submit SQL statements that get parsed and planned following which parallel tasks are scheduled to workers. Workers jointly process rows from the data sources and produce results that are returned to the client. Compared to the original Apache Hive execution model which used the Hadoop MapReduce mechanism on each query, Presto does not write intermediate results to disk resulting in a significant speed improvement. Presto is written in the Java programming language.
A single Presto query can combine data from multiple sources. Presto offers connectors to data sources including files in Hadoop Distributed File System, Amazon S3, MySQL, Apache Kafka, Apache Cassandra, PostgreSQL and Redis. Unlike other Hadoop distribution-specific tools, such as Cloudera Impala, Presto can work with any flavor of Hadoop or without it. Presto supports separation of compute and storage and may be deployed both on premises and in the cloud.