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Bigquery view vs materialized view

It is always faster to query a single table than any kind of view built on top of that table. However, the materialized view will be faster when you start joining multiple tables together as it stores the data resulting from the query and updates when the underlying tables change.

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the big advantage of a Materialized View is extremely fast retrieval of aggregate data, since it is precomputed and stored, at the expense of insert/update/delete. The database will keep the Materialized View in sync with the real data, no need to re-invent the wheel, let the database do it for you. Share. .

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Look my slide: http Google Analytics BigQuery Export Schema •Datasets: For each Analytics view that is enabled for BigQuery integration, a dataset is added using the view ID as the name. Innovate, optimize and amplify your SaaS applications using Google's data and machine learning solutions such as BigQuery , Looker, Spanner and Vertex AI..

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Materialized views run on top of a base table and cache the results. Essentially, the view will always serve the most recent version of the base table. Changes on the base table, its partitions or streamed data will force the view to re-read the updated parts (a whole table, partition or the delta). This enables far better performance when.

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