Perhaps we don't need the flatMap function and can directly compute the depth of the map type using case mt: MapType => 2 + math.max(computeMaxStackSizeForFlatten(mt.keyType), computeMaxStackSizeForFlatten(mt.v
* in spark-rapids-jni repo. * Note: * - This should be sync with `check_nested_depth` * - Map in cuDF is list of struct * * @param inputType the input type * @return the max stack size that inputType will use for this input type. */ def computeMaxStackSize(inputType: DataTyp...
EndpointTypes type Reference Feedback Package: @azure/arm-compute Defines values for EndpointTypes. TypeScript Copy type EndpointTypes = "WireServer" | "IMDS" English (New Zealand) Your Privacy Choices Theme Manage cookies Previous Versions Blog Contribute Privacy Terms of Use Trademarks © ...
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The main reason the industry is moving toward ELT is because cloud compute and storage are cheaper than ever. By transforming at the end of the process, data can be customized from the destination to suit the downstream use in the best way possible. ...
The IaaS cloud services delivery model is where a cloud service provider (CSP), like AWS or Azure, provides the basic compute (CPU and memory), network, and storage resources to a customer, over the internet, on an as-needed basis, and at a pay-as-you-go basis. In addition to virtua...
For example, Microsoft.ServiceBus/namespaces/queues is a child resource of Microsoft.ServiceBus/namespaces. When you move the parent resource, the child resource automatically moves with it. If you don't see a child resource in this article, you can assume that it moves with the parent ...
本文介绍 microsoft.compute/locations/publishers/artifacttypes/offers/skus/versions的每个 API 版本中更改的属性。 它仅涵盖部署期间可用的属性。 2022-03-01 未添加、更新或删除任何属性。 2021-11-01 未添加、更新或删除任何属性。 2021-07-01 未添加、更新或删除任何属性。 2021-04-01 ...
Apache Kafka addedTiered Storage to separate compute and storage. The capability enables more scalable, reliable, and cost-efficient enterprise architectures. Tiered Storage for Kafka enables a new Kafka cluster type: Storing Petabytes of data in the Kafka commit log in a cost-efficient way (like ...
since all tuples in a window have to be maintained and then iterated to compute an aggregate. Overlapping windows partly include the same tuples leading to redundant computations. Thus, research has proposed several techniques to optimize window aggregation (e.g., FlatFAT [84], Pairs [63], ...