Can you give an example of using the ParquteFile.iter_batches() API? I can see it returns a 'generator' class, but not sure how to iterate over the results to get at the underlying row data.
On Mon, Dec 27, 2021 at 11:33 AM David Li <[email protected]> wrote: > Ah, I'm sorry. I misremembered, I was recalling the implementation of > ReadOneRowGroup/ReadRowGroups, but iter_batches() boils down to > GetRecordBatchReader which does read at a finer granularity. > > -David > > On Mon, Dec 27, 2021, at 11:50, Micah Kornfield wrote: > > Just a shot in the dark, but how many row groups are there in that 1 GB > file? IIRC, the reader loads an entire row group's worth of rows at once. > > > Can you clarify what you mean by "loads" I thought it only loaded the > compressed data at once, and then read per page (I could be misremembering > or thinking this was an aspirational goal). > > On Fri, Dec 24, 2021 at 4:01 PM Partha Dutta <[email protected]> > wrote: > > I see 5 row groups. This parquet file contains 1.8 million records > > On Fri, Dec 24, 2021 at 4:51 PM David Li <[email protected]> wrote: > > > Just a shot in the dark, but how many row groups are there in that 1 GB > file? IIRC, the reader loads an entire row group's worth of rows at once. > > > -David > > On Fri, Dec 24, 2021, at 17:45, Partha Dutta wrote: > > I have a similar issue with trying to read huge 1GB parquet files from > Azure DataLake Storage. I'm trying to read the file in small chunks using > the ParquetFile.iter_batches method, but it seems like the entire file is > read into memory before the first batch is returned. I am using the Azure > SDK for python and another python package (pyarrowfs-adlgen2). Has anyone > faced a problem similar to what I am seeing, or is there a workaround? > > On Fri, Dec 24, 2021 at 2:11 PM Cindy McMullen <[email protected]> > wrote: > > Thanks, Arthur, this helps. The complete code example is: > > filename = 'gs://' + files[0] > gs = gcsfs.GCSFileSystem() > f = gs.open(filename) > pqf = pq.ParquetFile(f) > pqf.metadata > > > On Thu, Dec 23, 2021 at 1:48 AM Arthur Andres <[email protected]> > wrote: > > Hi Cindy, > > In your case you'd have to pass a GCS file instance to the ParquetFile > constructor. Something like this: > > source = fs.open_input_file(filename) > parquet_file = pq.ParquetFile(source) > > You can see how read_table does this in the source code: > https://github.com/apache/arrow/blob/16c442a03e2cf9c7748f0fa67b6694dbeb287fad/python/pyarrow/parquet.py#L1977 > > I hope this helps. > > > > On Thu, 23 Dec 2021 at 05:17, Cindy McMullen <[email protected]> > wrote: > > Hi - > > I need to drop down to the ParquetFile API so I can have better control > over batch size for reading huge Parquet files. The filename is: > > > *gs://graph_infra_steel_thread/output_pq/parquet/usersims/output-20211202-220329-20211202-220329-00-0012.parquet.snappy* > > This invocation fails: > *pqf = pq.ParquetFile(filename)* > "FileNotFoundError: [Errno 2] Failed to open local file > 'gs://graph_infra_steel_thread/output_pq/parquet/usersims/output-20211202-220329-20211202-220329-00-0012.parquet.snappy'. > Detail: [errno 2] No such file or directory" > > While this API, using the same, succeeds because I can specify 'gs' > filesystem. > *table = pq.read_table(filename, filesystem=gs, use_legacy_dataset=False) * > > I don't see a way to specify 'filesystem' on the ParquetFile API > <https://arrow.apache.org/docs/python/generated/pyarrow.parquet.ParquetFile.html#pyarrow.parquet.ParquetFile>. > Is there any way to read a GCS file using ParquetFile? > > If not, can you show me the code for reading batches using pq.read_table > or one of the other Arrow Parquet APIs > <https://arrow.apache.org/docs/python/api/formats.html#parquet-files>? > > Thanks - > > -- Cindy > > > > -- > Partha Dutta > [email protected] > > > -- > Partha Dutta > [email protected] > > >
