github snowflakedb/snowpark-python v0.2.0

latest releases: v1.14.0, v1.13.0, v1.12.1...
pre-release2 years ago

0.2.0 (2021-12-02)

New Features

  • Updated the Session.createDataFrame() method for creating a DataFrame from a Pandas DataFrame.
  • Added the Session.write_pandas() method for writing a Pandas DataFrame to a table in Snowflake and getting a Snowpark DataFrame object back.
  • Added new classes and methods for calling window functions.
  • Added the new functions cume_dist(), to find the cumulative distribution of a value with regard to other values within a window partition,
    and row_number(), which returns a unique row number for each row within a window partition.
  • Added functions for computing statistics for DataFrames in the DataFrameStatFunctions class.
  • Added functions for handling missing values in a DataFrame in the DataFrameNaFunctions class.
  • Added new methods rollup(), cube(), and pivot() to the DataFrame class.
  • Added the GroupingSets class, which you can use with the DataFrame groupByGroupingSets method to perform a SQL GROUP BY GROUPING SETS.
  • Added the new FileOperation(session)
    class that you can use to upload and download files to and from a stage.
  • Added the DataFrame.copy_into_table()
    method for loading data from files in a stage into a table.
  • In CASE expressions, the functions when() and otherwise()
    now accept Python types in addition to Column objects.
  • When you register a UDF you can now optionally set the replace parameter to True to overwrite an existing UDF with the same name.

Improvements

  • UDFs are now compressed before they are uploaded to the server. This makes them about 10 times smaller, which can help
    when you are using large ML model files.
  • When the size of a UDF is less than 8196 bytes, it will be uploaded as in-line code instead of uploaded to a stage.

Bug Fixes

  • Fixed an issue where the statement df.select(when(col("a") == 1, 4).otherwise(col("a"))), [Row(4), Row(2), Row(3)] raised an exception.
  • Fixed an issue where df.toPandas() raised an exception when a DataFrame was created from large local data.

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