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A Definitive Guide to Using BigQuery Efficiently

Towards Data Science

BigQuery basics and understanding costs ∘ Storage ∘ Compute · ? Like a dragon guarding its treasure, each byte stored and each query executed demands its share of gold coins. Join as we journey through the depths of cost optimization, where every byte is a precious coin. Photo by Konstantin Evdokimov on Unsplash ?

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Google BigQuery: A Game-Changing Data Warehousing Solution

ProjectPro

Since its public release in 2011, BigQuery has been marketed as a unique analytics cloud data warehouse tool that requires no virtual machines or hardware resources. BigQuery is a highly scalable data warehouse platform with a built-in query engine offered by Google Cloud Platform. What is Google BigQuery Used for?

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Deploying Kafka Streams and KSQL with Gradle – Part 2: Managing KSQL Implementations

Confluent

Building event streaming applications using KSQL is done with a series of SQL statements, as seen in this example. But I also wanted to introduce the pipeline concept: a group of SQL statements that work together to define an end-to-end process. Mapping streams and tables to a SQL script hierarchy. Table created. Not exactly.

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Deploying Kafka Streams and KSQL with Gradle – Part 3: KSQL User-Defined Functions and Kafka Streams

Confluent

KSQL provides a nice collection of built-in SQL functions for use in functional transformation logic when doing stream processing, whether the need is scalar functions for working with data a row at a time or aggregate functions used for grouping multiple rows into one summary record of output. Decode decode = new Decode() @Unroll.

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