December 2017
Beginner to intermediate
322 pages
6h 43m
English
book
Stream Analytics with Microsoft Azure
by Anindita Basak, Krishnaswamy Venkataraman, Ryan Murphy, Manpreet Singh
Content preview from Stream Analytics with Microsoft Azure
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Output source
Following is the full summary of output storage type and support for parallelization:
|
Storage Type |
Parallelizable |
Manual/Automatic |
|
Blobs, Tables, ADLS, Service Bus, and Azure Function |
Yes |
Automatic |
|
CosmosDB and Event Hub |
Yes |
Manual by specifying PARTITION BY field (usually Partition ID). For Event Hub verify the number of portions for inputs and output match to avoid cross-over between partitions. |
|
SQL, SQL DW, and PowerBI |
No |
Not applicable* |
As we reviewed in the previous section, using the right type of Inputs and Output with Partition ID can scale the query parallely. But not all jobs be parallelized. Let's get into the constructs of queries and query parallelization.
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