Improving stability with libcudf++, expanded SQL and more!

New Features:

• Support for AVG in distributed mode
• Added ability to use existing memory allocator
• Implemented unify_partitions function for preparing dask_cudf DataFrames prior to creating BlazingSQL tables
• Implemented ROUND function
• Implemented support for CASE with strings

Improvements:

• Local files can be referenced with relative file paths when creating tables.
• Automatic casting for joins on similar data types (i.e. joining an int32 with an int64 will cast the int32 to an int64)
• Updated AWS SDK version
• More changes to related to changes migration of libcudf to libcudf++
• Added docstrings to main python APIs

Bug Fixes:

• Fixed bug when for joining against empty DataFrame
• Fixed bug with GROUP BY ignoring nulls
• Fixed various issues related to creating tables from dask_cudf DataFrames
• Fixed various bugs with creating tables from Hive Cursor
• Fixed bugs related to new libcudf++ functionality
• Fixed bug in LIMIT statement
• Fixed bug in timestamp processing
• Fixed bug in SUM0 aggregation (which enables COUNT DISTINCT)
• Fixed bug when querying single file with multiple workers
• Fixed bug with distributed COUNT aggregation without GROUP BY
• Fixed bug when creating and querying a table with several Apache Parquet files and one is empty
• Fixed bug with joins with nulls in the join key columns

Other:

• Temporarily deprecated JSON reader. In the meantime we recommend using: cudf.read_json