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Dataiku DSS
You are viewing the documentation for version 11 of DSS.
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  • Schemas, storage types and meanings

Schemas, storage types and meanings¶

  • Definitions
    • Storage types
      • Why use precise storage types ?
    • Meanings
  • Basic usage
    • Changing meaning and storage type
      • Changing the storage type
      • Changing the meaning
      • Editing advanced schema
  • Schema for data preparation
    • Schema in visual analysis
    • Schema in prepare recipe
  • Creating schemas of datasets
    • Schema of new external datasets
      • SQL and Cassandra datasets
      • Text-based files datasets
      • “Typed” files datasets
    • Schema of managed datasets
    • Modifying the schema
  • Handling of schemas by recipes
    • Sample, Filter, Group, Window, Join, Split, Stack
    • Sync
    • Prepare
    • Hive, Impala, Pig, SQL
    • Python, R, PySpark, SparkR
    • Machine Learning (scoring)
    • SparkSQL
    • Shell
  • List of recognized meanings
    • Basic meanings
      • Text
      • Decimal
      • Integer
      • Boolean
      • Date / Dates (needs parsing)
      • Object / Array
      • Natural language
    • Geospatial meanings
      • Latitude / Longitude
      • Geopoint
      • Geometry
      • Country
      • US State
    • Web-specific meanings
    • Other meanings
  • User-defined meanings
    • Kinds of user-defined meanings
      • Declarative
      • Values list
      • Values mapping
      • Pattern
    • Autodetecting user-defined meanings
  • Handling and display of dates
    • Displaying dates
    • Handling of dates in SQL
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