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What are the pros and cons of the Apache Parquet format compared to . . . 30,36,2 Parquet files are most commonly compressed with the Snappy compression algorithm Snappy compressed files are splittable and quick to inflate Big data systems want to reduce file size on disk, but also want to make it quick to inflate the flies and run analytical queries Mutable nature of file Parquet files are immutable, as described
Python: save pandas data frame to parquet file - Stack Overflow Is it possible to save a pandas data frame directly to a parquet file? If not, what would be the suggested process? The aim is to be able to send the parquet file to another team, which they can
Inspect Parquet from command line - Stack Overflow How do I inspect the content of a Parquet file from the command line? The only option I see now is $ hadoop fs -get my-path local-file $ parquet-tools head local-file | less I would like to avoid
Extension of Apache parquet files, is it . pqt or . parquet? I wonder if there is a consensus regarding the extension of parquet files I have seen a shorter pqt extension, which has typical 3-letters (like in csv, tsv, txt, etc) and then there is a rather long (therefore unconventional (?)) parquet extension which is widely used
Updating values in apache parquet file - Stack Overflow I have a quite hefty parquet file where I need to change values for one of the column One way to do this would be to update those values in source text files and recreate parquet file but I'm wond
How to append new data to an existing parquet file? I have parquet files with some data in them I want to add more data to them frequently every day I want to do this without having to load the object to memory and then concatenate and write again
How to read a Parquet file into Pandas DataFrame? How to read a modestly sized Parquet data-set into an in-memory Pandas DataFrame without setting up a cluster computing infrastructure such as Hadoop or Spark? This is only a moderate amount of data that I would like to read in-memory with a simple Python script on a laptop
How do I get schema column names from parquet file? Also, Cloudera (which supports and contributes heavily to Parquet) has a nice page with examples on usage of hangxie's parquet-tools An example from that page for your use case: parquet-tools schema part-m-00000 parquet Check out the Cloudera page: Using Apache Parquet Data Files with CDH - Parquet File Structure