6/15/2023 0 Comments Snappy compression%timeit pd.read_parquet(path='file.parquet. ![]() %timeit pd.read_parquet(path='', engine='pyarrow') %timeit df.to_parquet(path='', compression='gzip', engine='pyarrow', index=True) %timeit df.to_parquet(path='', compression='snappy', engine='pyarrow', index=True) %timeit pd.read_parquet(path='', engine='pyarrow') Snappy is actually not splittable as bzip, but when used with file formats like parquet or Avro, instead of compressing the entire file, blocks inside the file format are compressed using snappy. %timeit df.to_parquet(path='', compression='snappy', engine='pyarrow', index=True) 1 Answer Sorted by: 2 You are compressing the plain string, as the compress function takes raw data. For example, running a basic test with a 5.6 MB CSV file called foo.csv results in a 2.4 MB Snappy. Google created Snappy because they needed something that offered very fast compression at the expense of the final size. | read | 3.22 ms | 3.44 ms | 6.8% slower |ĭata= np.c_, iris],Ĭolumns= iris + Google Snappy, previously known as Zippy, is widely used inside Google across a variety of systems. Results (small file, 4 KB, Iris dataset): +-+-+-+ Let's test speed and size with large and small parquet files in Python. The tradeoff depends on the retention period of the data. However, cloud compute is a one-time cost whereas cloud storage is a recurring cost. It's important to keep in mind that speed is essentially compute cost. See extensive research and benchmark code and results in this article ( Performance of various general compression algorithms – some of them are unbelievably fast!).īased on the data below, I'd say gzip wins outside of scenarios like streaming, where write-time latency would be important. LZO focus on decompression speed at low CPU usage and higher compression at the cost of more CPU.įor longer term/static storage, the GZip compression is still better. ![]() GZIP compresses data 30% more as compared to Snappy and 2x more CPU when reading GZIP data compared to one that is consuming Snappy data. If you need your compressed data to be splittable, BZip2, LZO, and Snappy formats are splittable, but GZip is not. Jordan Neely, 30, died from compression of the neck, the city’s medical examiner determined Wednesday, ruling the death a homicide. It is worth running tests to see if you detect a significant difference. The Short List is a snappy USA TODAY news roundup. ![]() Snappy or LZO are a better choice for hot data, which is accessed frequently. GZip is often a good choice for cold data, which is accessed infrequently. GZIP compression uses more CPU resources than Snappy or LZO, but provides a higher compression ratio.
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