docs: Hydration details and concepts page - #38168
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| materialized view (public preview) and replacing the existing view in | ||
| place](/transform-data/updating-materialized-views/replace-materialized-view/) | ||
| may be simpler, but briefly reduces freshness. | ||
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Did not include compute_hydration_concurrency as a strategy
| Hydration primarily impacts memory usage, and its speed scales with cluster | ||
| size. Some hydration-related strategies you may want to consider: | ||
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| - Add an [`AUTO SCALING STRATEGY (ON HYDRATION)`](/sql/alter-cluster/) to your |
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probably will move it to the hydration-details.yml later on.
| then removes it once a steady-size replica catches up. You pay for the burst | ||
| replica while it is provisioned, but not at steady state. | ||
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| - Split materialized views and indexes across multiple clusters. Each cluster |
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I like this! I'd recommend checking out what @tylerhartwig did to shard MVs well. There's a number of strategies you can employ and I think sharing more details would help
| require a significant amount of CPU and memory. | ||
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| - During hydration (both initial and subsequent rehydrations), materialized | ||
| - During hydration (both initial hydration and subsequent rehydrations), materialized |
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I'm not sure where to put this, but rehydration technically uses more memory! I'll let @antiguru confirm, but my understanding is:
- If you create a cluster for a first time with 10 MVs, you'll use X memory
- If you restart that cluster and have to rehydrate the 10 MVs, you'll need 2X memory
It might be worth splitting up those concepts and specifying the memory requirements for both
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Oh, heh .. I think I clobbered that line where we stated "materialized views require memory proportional to both the input and output." (i.e., your 2X 😄 ) But, will also wait for confirmation.
2 participants
https://preview.materialize.com/materialize/38168/concepts/hydration/
Part 1 of Hydration content:
Once approved and merged, Part 2 will include the approved details in appropriate places.