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https://issues.apache.org/jira/browse/ARROW-5647?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16870857#comment-16870857
]
Simon Lidberg commented on ARROW-5647:
--------------------------------------
I tested now with accessing the file using /dbfs/mnt/aa/example.parquet it
fails but this time with another error:
Version:1.0 StartHTML:000000221 EndHTML:000014581 StartFragment:000001384
EndFragment:000014435 StartSelection:000001384 EndSelection:000014435
SourceURL:https://westeurope.azuredatabricks.net/?o=4812138293037155 ADLS2_Test
- Databricks
---------------------------------------------------------------------------
ArrowIOError Traceback (most recent call last) <command-4042920808160098> in
<module>() ----> 1 pddf2 = pd.read_parquet("/dbfs/mnt/aa/example2.parquet",
engine='pyarrow') 2 display(pddf2)
/databricks/python/lib/python3.5/site-packages/pandas/io/parquet.py in
read_parquet(path, engine, columns, **kwargs) 280 281 impl =
get_engine(engine) --> 282 return impl.read(path, columns=columns, **kwargs)
/databricks/python/lib/python3.5/site-packages/pandas/io/parquet.py in
read(self, path, columns, **kwargs) 127 kwargs['use_pandas_metadata'] = True
128 result = self.api.parquet.read_table(path, columns=columns, --> 129
**kwargs).to_pandas() 130 if should_close: 131 try:
/databricks/python/lib/python3.5/site-packages/pyarrow/parquet.py in
read_table(source, columns, use_threads, metadata, use_pandas_metadata,
memory_map, filesystem) 1150 return fs.read_parquet(path, columns=columns,
1151 use_threads=use_threads, metadata=metadata, -> 1152
use_pandas_metadata=use_pandas_metadata) 1153 1154 pf = ParquetFile(source,
metadata=metadata)
/databricks/python/lib/python3.5/site-packages/pyarrow/filesystem.py in
read_parquet(self, path, columns, metadata, schema, use_threads,
use_pandas_metadata) 177 from pyarrow.parquet import ParquetDataset 178
dataset = ParquetDataset(path, schema=schema, metadata=metadata, --> 179
filesystem=self) 180 return dataset.read(columns=columns,
use_threads=use_threads, 181 use_pandas_metadata=use_pandas_metadata)
/databricks/python/lib/python3.5/site-packages/pyarrow/parquet.py in
__init__(self, path_or_paths, filesystem, schema, metadata, split_row_groups,
validate_schema, filters, metadata_nthreads, memory_map) 956 957 if
validate_schema: --> 958 self.validate_schemas() 959 960 if filters is not
None: /databricks/python/lib/python3.5/site-packages/pyarrow/parquet.py in
validate_schemas(self) 967 self.schema = self.common_metadata.schema 968
else: --> 969 self.schema = self.pieces[0].get_metadata().schema 970 elif
self.schema is None: 971 self.schema = self.metadata.schema
/databricks/python/lib/python3.5/site-packages/pyarrow/parquet.py in
get_metadata(self, open_file_func) 500 f = self._open(open_file_func) 501
else: --> 502 f = self.open() 503 return f.metadata 504
/databricks/python/lib/python3.5/site-packages/pyarrow/parquet.py in open(self)
518 Returns instance of ParquetFile 519 """ --> 520 reader =
self.open_file_func(self.path) 521 if not isinstance(reader, ParquetFile):
522 reader = ParquetFile(reader)
/databricks/python/lib/python3.5/site-packages/pyarrow/parquet.py in
open_file(path, meta) 1054 return ParquetFile(path, metadata=meta, 1055
memory_map=self.memory_map, -> 1056 common_metadata=self.common_metadata) 1057
else: 1058 def open_file(path, meta=None):
/databricks/python/lib/python3.5/site-packages/pyarrow/parquet.py in
__init__(self, source, metadata, common_metadata, memory_map) 128
memory_map=True): 129 self.reader = ParquetReader() --> 130
self.reader.open(source, use_memory_map=memory_map, metadata=metadata) 131
self.common_metadata = common_metadata 132 self._nested_paths_by_prefix =
self._build_nested_paths()
/databricks/python/lib/python3.5/site-packages/pyarrow/_parquet.cpython-35m-x86_64-linux-gnu.so
in pyarrow._parquet.ParquetReader.open()
/databricks/python/lib/python3.5/site-packages/pyarrow/lib.cpython-35m-x86_64-linux-gnu.so
in pyarrow.lib.check_status() ArrowIOError: Invalid parquet file. Corrupt
footer.
My entire test code is as follows:
from pyspark.sql import *
# Create test data
row1 = Row(id='1', name='Alpha')
row2 = Row(id='2', name='Beta')
row3 = Row(id='3', name='Gamma')
row4 = Row(id='4', name='Delta')
df = spark.createDataFrame([row1, row2, row3, row4])
display(df)
# Write the data to the mount point
df.write.parquet("/mnt/aa/example2.parquet")
# Try reading using pandas read_parquet
pddf2 = pd.read_parquet("/dbfs/mnt/aa/example.parquet", engine='pyarrow')
display(pddf2)
The same file can be read using
df2 = spark.read.parquet("/mnt/aa/example.parquet")
pddf = df2.toPandas()
type(pddf)
> [Python] Accessing a file from Databricks using pandas read_parquet using the
> pyarrow engine fails with : Passed non-file path: /mnt/aa/example.parquet
> --------------------------------------------------------------------------------------------------------------------------------------------------------
>
> Key: ARROW-5647
> URL: https://issues.apache.org/jira/browse/ARROW-5647
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 0.13.0
> Environment: Azure Databricks
> Reporter: Simon Lidberg
> Priority: Major
> Attachments: arrow_error.txt
>
>
> When trying to access a file using a mount point pointing to an Azure blob
> storage account the code fails with the following error:
> {color:#8b0000}OSError{color}: Passed non-file path: /mnt/aa/example.parquet
> {color:#8b0000}---------------------------------------------------------------------------{color}
> {color:#8b0000}OSError{color} Traceback (most recent call last)
> {color:#006400}<command-1848295812523966>{color} in
> {color:#4682b4}<module>{color}{color:#00008b}(){color} {color:#006400}---->
> 1{color} pddf2 {color:#AA4B00}={color}
> pd{color:#AA4B00}.{color}read_parquet{color:#AA4B00}({color}{color:#00008b}"/mnt/aa/example.parquet"{color}{color:#AA4B00},{color}
>
> engine{color:#AA4B00}={color}{color:#00008b}'pyarrow'{color}{color:#AA4B00}){color}
> {color:#006400} 2{color}
> display{color:#AA4B00}({color}pddf2{color:#AA4B00}){color}
> {color:#006400}/databricks/python/lib/python3.5/site-packages/pandas/io/parquet.py{color}
> in {color:#4682b4}read_parquet{color}{color:#00008b}(path, engine, columns,
> **kwargs){color} {color:#006400} 280{color} {color:#006400} 281{color} impl
> {color:#AA4B00}={color}
> get_engine{color:#AA4B00}({color}engine{color:#AA4B00}){color}
> {color:#006400}--> 282{color} {color:#006400}return{color}
> impl{color:#AA4B00}.{color}read{color:#AA4B00}({color}path{color:#AA4B00},{color}
> columns{color:#AA4B00}={color}columns{color:#AA4B00},{color}
> {color:#AA4B00}**{color}kwargs{color:#AA4B00}){color}
> {color:#006400}/databricks/python/lib/python3.5/site-packages/pandas/io/parquet.py{color}
> in {color:#4682b4}read{color}{color:#00008b}(self, path, columns,
> **kwargs){color} {color:#006400} 127{color}
> kwargs{color:#AA4B00}[{color}{color:#00008b}'use_pandas_metadata'{color}{color:#AA4B00}]{color}
> {color:#AA4B00}={color} {color:#006400}True{color} {color:#006400}
> 128{color} result = self.api.parquet.read_table(path, columns=columns,
> {color:#006400}--> 129{color}{color:#AA4B00} **kwargs).to_pandas()
> {color}{color:#006400} 130{color} {color:#006400}if{color}
> should_close{color:#AA4B00}:{color} {color:#006400} 131{color}
> {color:#006400}try{color}{color:#AA4B00}:{color}
> {color:#006400}/databricks/python/lib/python3.5/site-packages/pyarrow/parquet.py{color}
> in {color:#4682b4}read_table{color}{color:#00008b}(source, columns,
> use_threads, metadata, use_pandas_metadata, memory_map, filesystem){color}
> {color:#006400} 1150{color} return fs.read_parquet(path, columns=columns,
> {color:#006400} 1151{color}
> use_threads{color:#AA4B00}={color}use_threads{color:#AA4B00},{color}
> metadata{color:#AA4B00}={color}metadata{color:#AA4B00},{color}
> {color:#006400}-> 1152{color}{color:#AA4B00}
> use_pandas_metadata=use_pandas_metadata) {color}{color:#006400} 1153{color}
> {color:#006400} 1154{color} pf {color:#AA4B00}={color}
> ParquetFile{color:#AA4B00}({color}source{color:#AA4B00},{color}
> metadata{color:#AA4B00}={color}metadata{color:#AA4B00}){color}
> {color:#006400}/databricks/python/lib/python3.5/site-packages/pyarrow/filesystem.py{color}
> in {color:#4682b4}read_parquet{color}{color:#00008b}(self, path, columns,
> metadata, schema, use_threads, use_pandas_metadata){color} {color:#006400}
> 177{color} {color:#006400}from{color} pyarrow{color:#AA4B00}.{color}parquet
> {color:#006400}import{color} ParquetDataset {color:#006400} 178{color}
> dataset = ParquetDataset(path, schema=schema, metadata=metadata,
> {color:#006400}--> 179{color}{color:#AA4B00} filesystem=self)
> {color}{color:#006400} 180{color} return dataset.read(columns=columns,
> use_threads=use_threads, {color:#006400} 181{color}
> use_pandas_metadata=use_pandas_metadata)
> {color:#006400}/databricks/python/lib/python3.5/site-packages/pyarrow/parquet.py{color}
> in {color:#4682b4}__init__{color}{color:#00008b}(self, path_or_paths,
> filesystem, schema, metadata, split_row_groups, validate_schema, filters,
> metadata_nthreads, memory_map){color} {color:#006400} 933{color}
> self{color:#AA4B00}.{color}metadata_path{color:#AA4B00}){color}
> {color:#AA4B00}={color} _make_manifest{color:#AA4B00}({color} {color:#006400}
> 934{color} path_or_paths{color:#AA4B00},{color}
> self{color:#AA4B00}.{color}fs{color:#AA4B00},{color}
> metadata_nthreads{color:#AA4B00}={color}metadata_nthreads{color:#AA4B00},{color}
> {color:#006400}--> 935{color}{color:#AA4B00}
> open_file_func=self._open_file_func) {color}{color:#006400} 936{color}
> {color:#006400} 937{color} {color:#006400}if{color}
> self{color:#AA4B00}.{color}common_metadata_path {color:#006400}is{color}
> {color:#006400}not{color} {color:#006400}None{color}{color:#AA4B00}:{color}
> {color:#006400}/databricks/python/lib/python3.5/site-packages/pyarrow/parquet.py{color}
> in {color:#4682b4}_make_manifest{color}{color:#00008b}(path_or_paths, fs,
> pathsep, metadata_nthreads, open_file_func){color} {color:#006400}
> 1108{color} {color:#006400}if{color} {color:#006400}not{color}
> fs{color:#AA4B00}.{color}isfile{color:#AA4B00}({color}path{color:#AA4B00}){color}{color:#AA4B00}:{color}
> {color:#006400} 1109{color} raise IOError('Passed non-file path: \{0}'
> {color:#006400}-> 1110{color}{color:#AA4B00} .format(path))
> {color}{color:#006400} 1111{color} piece {color:#AA4B00}={color}
> ParquetDatasetPiece{color:#AA4B00}({color}path{color:#AA4B00},{color}
> open_file_func{color:#AA4B00}={color}open_file_func{color:#AA4B00}){color}
> {color:#006400} 1112{color}
> pieces{color:#AA4B00}.{color}append{color:#AA4B00}({color}piece{color:#AA4B00}){color}
> {color:#8b0000}OSError{color}: Passed non-file path: /mnt/aa/example.parquet
>
> I am using the following code from a Databricks notebook to reproduce the
> issue:
> {color:#005000}%sh
> {color}
> {color:#005000}sudo apt-get -y install python3-pip
> /databricks/python3/bin/pip3 uninstall pandas -y
> /databricks/python3/bin/pip3 uninstall numpy -y{color}
> {color:#005000}{color:#b08000}/databricks/python3/bin/pip3 uninstall pyarrow
> -y{color}{color}
>
>
> {color:#005000}{color:#b08000}{color:#b08000}%sh
> /databricks/python3/bin/pip3 install numpy==1.14.0
> /databricks/python3/bin/pip3 install pandas==0.24.1
> /databricks/python3/bin/pip3 install pyarrow==0.13.0{color}{color}{color}
>
> {color:#005000}{color:#b08000}{color:#b08000}{color:#b08000}dbutils.fs.mount(
> source = "wasbs://<mycontainer>@<mystorageaccount>.blob.core.windows.net",
> mount_point = "/mnt/aa",
> extra_configs =
> \{"fs.azure.account.key.<mystorageaccount>.blob.core.windows.net":dbutils.secrets.get(scope
> = "storage", key = "blob_key")}){color}{color}{color}{color}
>
> {color:#005000}{color:#b08000}{color:#b08000}{color:#b08000}pddf2 =
> pd.read_parquet("/mnt/aa/example.parquet", engine='pyarrow')
> display(pddf2){color}{color}{color}{color}
>
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