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


We could certainly develop some tools in C++ and/or Python to assist
with the compaction workflows. If you have an idea about how these
might look and be generally useful, please feel free to propose in a
JIRA issue

On Wed, Dec 19, 2018 at 9:09 AM Joel Pfaff <joel.pfaff@xxxxxxxxx> wrote:
>
> 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.
> > >>>
> >