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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

Of course, a local Maven repository is not fit for real environments, but Gradle supports all major Maven repository servers, as well as AWS S3 and Google Cloud Storage as Maven artifact repositories. zip Zip file size: 3593 bytes, number of entries: 9 drwxr-xr-x 2.0 6 objects dropped. 6 objects created. m2 directory.

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

Confluent

jar Zip file size: 5849 bytes, number of entries: 5. jar Zip file size: 11405084 bytes, number of entries: 7422. It can then send that activity to cloud services like AWS Kinesis, Amazon S3, Cloud Pub/Sub, or Google Cloud Storage and a few JDBC sources. And of course, it can send data to Kafka.

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