Parquet performance tuning: the missing guide
Parquet performance tuning focuses on optimizing Parquet reads by leveraging columnar organization, encoding, and filtering techniques. Statistics and dictionary filtering can eliminate unnecessary data reads by filtering at the row group and page levels. However, these optimizations require columns to be sorted and fully dictionary encoded within files. Increasing dictionary size thresholds and d
Engineering Data Analytics with Presto and Parquet at Uber
Data / MLEngineering Data Analytics with Presto and Apache Parquet at UberJuly 11, 2017 / Global From determining the most convenient rider pickup points to predicting the fastest routes, Uber uses data-driven analytics to create seamless trip experiences. Within engineering, analytics inform decision-making processes across the board. As we expand to new markets, the ability to accurately and qui
PyFormat: Using % and .format() for great good!
Python has had awesome string formatters for many years but the documentation on them is far too theoretic and technical. With this site we try to show you the most common use-cases covered by the old and new style string formatting API with practical examples. All examples on this page work out of the box with with Python 2.7, 3.2, 3.3, 3.4, and 3.5 without requiring any additional libraries. Fur
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Tuning Parquet file performance | Dremio
Presto Driver,Split and Pipeline
