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Re: How to append to parquet file periodically and read intermediate data - pyarrow.lib.ArrowIOError: Invalid parquet file. Corrupt footer.


Unfortunately I cannot use kudu in my projects, I would have loved to give
it a try. I did not know about hudi, it seems very similar to what we do
(Parquet + Avro), I will have a look.
I am following the iceberg project very closely, because it appears to
solve a lot of problems that we face on a regular basis.
I am really excited to learn that the arrow and iceberg projects could work
together and I can hope for a lot of good things coming out of these.

On Wed, Dec 19, 2018 at 2:52 PM Uwe L. Korn <uwelk@xxxxxxxxxx> wrote:

> This can also be solved by using a table format like
> https://github.com/uber/hudi or
> https://github.com/apache/incubator-iceberg where the latter has a PR
> open for a basic Python implementation with pyarrow.
>
> These table formats support using Avro and Parquet seamlessly together
> without the reader needing to take care of the storage format.
>
> Uwe
>
> > Am 19.12.2018 um 14:47 schrieb Wes McKinney <wesmckinn@xxxxxxxxx>:
> >
> > This turns out to be a very common problem (landing incremental
> > updates, dealing with compaction and small files). It's part of the
> > reason that systems like Apache Kudu were developed, e.g.
> >
> >
> https://blog.cloudera.com/blog/2015/11/how-to-ingest-and-query-fast-data-with-impala-without-kudu/
> >
> > If you have to use file storage, then figuring out a scheme to compact
> > Parquet files (e.g. once per hour, once per day) will definitely be
> > worth it compared with using a slower file format (like Avro)
> >
> > - Wes
> >
> >> On Wed, Dec 19, 2018 at 7:37 AM Joel Pfaff <joel.pfaff@xxxxxxxxx>
> wrote:
> >>
> >> Hello,
> >>
> >> For my company's usecases, we have found that the number of files was a
> >> critical part of the time spent doing the execution plan, so we found
> the
> >> idea of very regularly writing small parquet files to be rather
> inefficient.
> >>
> >> There are some formats that support an `append` semantic (I have tested
> >> successfully with avro, but there are a couple others that could be used
> >> similarly).
> >> So we had a few cases where we were aggregating data in a `current
> table`
> >> in set of avro files, and rewriting all of it in few parquet files at
> the
> >> end of the day.
> >> This allowed us to have files that have been prepared to optimize their
> >> querying performance (file size, row group size, sorting per column) by
> >> maximizing the ability to benefit from the statistics.
> >> And our queries were doing an UNION between "optimized for speed"
> history
> >> tables and "optimized for latency" current tables, when the query
> timeframe
> >> was crossing the boundaries of the current day.
> >>
> >> Regards, Joel
> >>
> >> On Wed, Dec 19, 2018 at 2:14 PM Francois Saint-Jacques <
> >> fsaintjacques@xxxxxxxxxxxxxxx> wrote:
> >>
> >>> Hello Darren,
> >>>
> >>> what Uwe suggests is usually the way to go, your active process writes
> to a
> >>> new file every time. Then you have a parallel process/thread that does
> >>> compaction of smaller files in the background such that you don't have
> too
> >>> many files.
> >>>
> >>>> On Wed, Dec 19, 2018 at 7:59 AM Uwe L. Korn <uwelk@xxxxxxxxxx> wrote:
> >>>>
> >>>> Hello Darren,
> >>>>
> >>>> you're out of luck here. Parquet files are immutable and meant for
> batch
> >>>> writes. Once they're written you cannot modify them anymore. To load
> >>> them,
> >>>> you need to know their metadata which is in the footer. The footer is
> >>>> always at the end of the file and written once you call close.
> >>>>
> >>>> Your use case is normally fulfilled by continously starting new files
> and
> >>>> reading them back in using the ParquetDataset class
> >>>>
> >>>> Cheers
> >>>> Uwe
> >>>>
> >>>> Am 18.12.2018 um 21:03 schrieb Darren Gallagher <dazzag@xxxxxxxxx>:
> >>>>
> >>>>>> [Cross posted from https://github.com/apache/arrow/issues/3203]
> >>>>>>
> >>>>>> I'm adding new data to a parquet file every 60 seconds using this
> >>> code:
> >>>>>>
> >>>>>> import os
> >>>>>> import json
> >>>>>> import time
> >>>>>> import requests
> >>>>>> import pandas as pd
> >>>>>> import numpy as np
> >>>>>> import pyarrow as pa
> >>>>>> import pyarrow.parquet as pq
> >>>>>>
> >>>>>> api_url = 'https://opensky-network.org/api/states/all'
> >>>>>>
> >>>>>> cols = ['icao24', 'callsign', 'origin', 'time_position',
> >>>>>>       'last_contact', 'longitude', 'latitude',
> >>>>>>       'baro_altitude', 'on_ground', 'velocity', 'true_track',
> >>>>>>       'vertical_rate', 'sensors', 'geo_altitude', 'squawk',
> >>>>>>       'spi', 'position_source']
> >>>>>>
> >>>>>> def get_new_flight_info(writer):
> >>>>>>   print("Requesting new data")
> >>>>>>   req = requests.get(api_url)
> >>>>>>   content = req.json()
> >>>>>>
> >>>>>>   states = content['states']
> >>>>>>   df = pd.DataFrame(states, columns = cols)
> >>>>>>   df['timestamp'] = content['time']
> >>>>>>   print("Found {} new items".format(len(df)))
> >>>>>>
> >>>>>>   table = pa.Table.from_pandas(df)
> >>>>>>   if writer is None:
> >>>>>>       writer = pq.ParquetWriter('openskyflights.parquet',
> >>> table.schema)
> >>>>>>   writer.write_table(table=table)
> >>>>>>   return writer
> >>>>>>
> >>>>>> if __name__ == '__main__':
> >>>>>>   writer = None
> >>>>>>   while (not os.path.exists('opensky.STOP')):
> >>>>>>       writer = get_new_flight_info(writer)
> >>>>>>       time.sleep(60)
> >>>>>>
> >>>>>>   if writer:
> >>>>>>       writer.close()
> >>>>>>
> >>>>>> This is working fine and the file grows every 60 seconds.
> >>>>>> However unless I force the loop to exit I am unable to use the
> parquet
> >>>>>> file. In a separate terminal I try to access the parquet file using
> >>> this
> >>>>>> code:
> >>>>>>
> >>>>>> import pandas as pd
> >>>>>> import pyarrow.parquet as pq
> >>>>>>
> >>>>>> table = pq.read_table("openskyflights.parquet")
> >>>>>> df = table.to_pandas()
> >>>>>> print(len(df))
> >>>>>>
> >>>>>> which results in this error:
> >>>>>>
> >>>>>> Traceback (most recent call last):
> >>>>>> File "checkdownloadsize.py", line 7, in <module>
> >>>>>>   table = pq.read_table("openskyflights.parquet")
> >>>>>> File
> >>>>
> >>>
> "/home/xxxx/.local/share/virtualenvs/opensky-WcPvsoLj/lib/python3.5/site-packages/pyarrow/parquet.py",
> >>>> line 1074, in read_table
> >>>>>>   use_pandas_metadata=use_pandas_metadata)
> >>>>>> File
> >>>>
> >>>
> "/home/xxxx/.local/share/virtualenvs/opensky-WcPvsoLj/lib/python3.5/site-packages/pyarrow/filesystem.py",
> >>>> line 182, in read_parquet
> >>>>>>   filesystem=self)
> >>>>>> File
> >>>>
> >>>
> "/home/xxxx/.local/share/virtualenvs/opensky-WcPvsoLj/lib/python3.5/site-packages/pyarrow/parquet.py",
> >>>> line 882, in __init__
> >>>>>>   self.validate_schemas()
> >>>>>> File
> >>>>
> >>>
> "/home/xxxx/.local/share/virtualenvs/opensky-WcPvsoLj/lib/python3.5/site-packages/pyarrow/parquet.py",
> >>>> line 895, in validate_schemas
> >>>>>>   self.schema = self.pieces[0].get_metadata(open_file).schema
> >>>>>> File
> >>>>
> >>>
> "/home/xxxx/.local/share/virtualenvs/opensky-WcPvsoLj/lib/python3.5/site-packages/pyarrow/parquet.py",
> >>>> line 453, in get_metadata
> >>>>>>   return self._open(open_file_func).metadata
> >>>>>> File
> >>>>
> >>>
> "/home/xxxx/.local/share/virtualenvs/opensky-WcPvsoLj/lib/python3.5/site-packages/pyarrow/parquet.py",
> >>>> line 459, in _open
> >>>>>>   reader = open_file_func(self.path)
> >>>>>> File
> >>>>
> >>>
> "/home/xxxx/.local/share/virtualenvs/opensky-WcPvsoLj/lib/python3.5/site-packages/pyarrow/parquet.py",
> >>>> line 984, in open_file
> >>>>>>   common_metadata=self.common_metadata)
> >>>>>> File
> >>>>
> >>>
> "/home/xxxx/.local/share/virtualenvs/opensky-WcPvsoLj/lib/python3.5/site-packages/pyarrow/parquet.py",
> >>>> line 102, in __init__
> >>>>>>   self.reader.open(source, metadata=metadata)
> >>>>>> File "pyarrow/_parquet.pyx", line 639, in
> >>>> pyarrow._parquet.ParquetReader.open
> >>>>>> File "pyarrow/error.pxi", line 83, in pyarrow.lib.check_status
> >>>>>> pyarrow.lib.ArrowIOError: Invalid parquet file. Corrupt footer.
> >>>>>>
> >>>>>> Is there a way to achieve this?
> >>>>>> I'm assuming that if I call writer.close() in the while loop then it
> >>>> will
> >>>>>> prevent any further data being written to the file? Is there some
> kind
> >>>> of
> >>>>>> "flush" operation that can be used to ensure all data is written to
> >>> disk
> >>>>>> and available to other processes or threads that want to read the
> >>> data?
> >>>>>>
> >>>>>> Thanks
> >>>>>>
> >>>>
> >>>>
> >>>
> >>> --
> >>> Sent from my jetpack.
> >>>
>