Table of Contents

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  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Aggregator transformation
  6. Cleanse transformation
  7. Data Masking transformation
  8. Data Services transformation
  9. Deduplicate transformation
  10. Expression transformation
  11. Filter transformation
  12. Hierarchy Builder transformation
  13. Hierarchy Parser transformation
  14. Hierarchy Processor transformation
  15. Input transformation
  16. Java transformation
  17. Java transformation API reference
  18. Joiner transformation
  19. Labeler transformation
  20. Lookup transformation
  21. Machine Learning transformation
  22. Mapplet transformation
  23. Normalizer transformation
  24. Output transformation
  25. Parse transformation
  26. Python transformation
  27. Rank transformation
  28. Router transformation
  29. Rule Specification transformation
  30. Sequence Generator transformation
  31. Sorter transformation
  32. SQL transformation
  33. Structure Parser transformation
  34. Transaction Control transformation
  35. Union transformation
  36. Velocity transformation
  37. Verifier transformation
  38. Web Services transformation

Transformations

Transformations

Configuring bulk requests

Configuring bulk requests

Configure bulk requests to optimize performance by combining multiple requests into one request that the Machine Learning transformation sends to the machine learning model. Bulk requests can improve performance by reducing processing overhead and the amount of time that it takes to communicate with the model.
To create a bulk request, the Machine Learning transformation selects the highest-level array field in the request schema. In the JSON request body for the bulk request, the transformation combines request rows as elements of the selected array field so that one JSON request body contains data for multiple requests. You can configure bulk request options to determine how much data each bulk request contains.
For example, the request schema might have the following structure:
The request schema contains a struct called instances. The instances struct contains a nested array called data which contains another nested array called features.
The Machine Learning transformation selects the
data
array as the highest-level array field to combine requests. If you configure each bulk request to send 2 MB of data to the machine learning model, the Machine Learning transformation configures the
data
array in the JSON request body to include data for 2 MB of request rows.
The highest-level array cannot have sibling array fields. If the highest-level array has a sibling field of a primitive data type, the data in the sibling field will not be combined. Instead, one random record in the sibling field will be sent to the machine learning model.
To create a bulk response, the machine learning endpoint must combine response rows as elements of the highest-level array in the response schema. The Machine Learning transformation parses the array into output rows. Review the bulk request options to verify which field the Machine Learning transformation will parse.
To use bulk requests in the Machine Learning transformation, the machine learning endpoint must be configured to accept bulk requests and send bulk responses.

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