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import os
import posixpath
import sys
from pyarrow.util import implements
from pyarrow.filesystem import FileSystem
import pyarrow.lib as lib
class HadoopFileSystem(lib.HadoopFileSystem, FileSystem):
"""
FileSystem interface for HDFS cluster. See pyarrow.hdfs.connect for full
connection details
"""
def __init__(self, host="default", port=0, user=None, kerb_ticket=None,
driver='libhdfs', extra_conf=None):
if driver == 'libhdfs':
_maybe_set_hadoop_classpath()
self._connect(host, port, user, kerb_ticket, driver, extra_conf)
def __reduce__(self):
return (HadoopFileSystem, (self.host, self.port, self.user,
self.kerb_ticket, self.driver,
self.extra_conf))
def _isfilestore(self):
"""
Returns True if this FileSystem is a unix-style file store with
directories.
"""
return True
@implements(FileSystem.isdir)
def isdir(self, path):
return super(HadoopFileSystem, self).isdir(path)
@implements(FileSystem.isfile)
def isfile(self, path):
return super(HadoopFileSystem, self).isfile(path)
[docs] @implements(FileSystem.delete)
def delete(self, path, recursive=False):
return super(HadoopFileSystem, self).delete(path, recursive)
[docs] def mkdir(self, path, **kwargs):
"""
Create directory in HDFS
Parameters
----------
path : string
Directory path to create, including any parent directories
Notes
-----
libhdfs does not support create_parents=False, so we ignore this here
"""
return super(HadoopFileSystem, self).mkdir(path)
@implements(FileSystem.rename)
def rename(self, path, new_path):
return super(HadoopFileSystem, self).rename(path, new_path)
[docs] @implements(FileSystem.exists)
def exists(self, path):
return super(HadoopFileSystem, self).exists(path)
[docs] def ls(self, path, detail=False):
"""
Retrieve directory contents and metadata, if requested.
Parameters
----------
path : HDFS path
detail : boolean, default False
If False, only return list of paths
Returns
-------
result : list of dicts (detail=True) or strings (detail=False)
"""
return super(HadoopFileSystem, self).ls(path, detail)
def walk(self, top_path):
"""
Directory tree generator for HDFS, like os.walk
Parameters
----------
top_path : string
Root directory for tree traversal
Returns
-------
Generator yielding 3-tuple (dirpath, dirnames, filename)
"""
contents = self.ls(top_path, detail=True)
directories, files = _libhdfs_walk_files_dirs(top_path, contents)
yield top_path, directories, files
for dirname in directories:
for tup in self.walk(self._path_join(top_path, dirname)):
yield tup
def _maybe_set_hadoop_classpath():
if 'hadoop' in os.environ.get('CLASSPATH', ''):
return
if 'HADOOP_HOME' in os.environ:
if sys.platform != 'win32':
classpath = _derive_hadoop_classpath()
else:
hadoop_bin = '{0}/bin/hadoop'.format(os.environ['HADOOP_HOME'])
classpath = _hadoop_classpath_glob(hadoop_bin)
else:
classpath = _hadoop_classpath_glob('hadoop')
os.environ['CLASSPATH'] = classpath.decode('utf-8')
def _derive_hadoop_classpath():
import subprocess
find_args = ('find', os.environ['HADOOP_HOME'], '-name', '*.jar')
find = subprocess.Popen(find_args, stdout=subprocess.PIPE)
xargs_echo = subprocess.Popen(('xargs', 'echo'),
stdin=find.stdout,
stdout=subprocess.PIPE)
jars = subprocess.check_output(('tr', "' '", "':'"),
stdin=xargs_echo.stdout)
hadoop_conf = os.environ["HADOOP_CONF_DIR"] \
if "HADOOP_CONF_DIR" in os.environ \
else os.environ["HADOOP_HOME"] + "/etc/hadoop"
return (hadoop_conf + ":").encode("utf-8") + jars
def _hadoop_classpath_glob(hadoop_bin):
import subprocess
hadoop_classpath_args = (hadoop_bin, 'classpath', '--glob')
return subprocess.check_output(hadoop_classpath_args)
def _libhdfs_walk_files_dirs(top_path, contents):
files = []
directories = []
for c in contents:
scrubbed_name = posixpath.split(c['name'])[1]
if c['kind'] == 'file':
files.append(scrubbed_name)
else:
directories.append(scrubbed_name)
return directories, files
def connect(host="default", port=0, user=None, kerb_ticket=None,
driver='libhdfs', extra_conf=None):
"""
Connect to an HDFS cluster. All parameters are optional and should
only be set if the defaults need to be overridden.
Authentication should be automatic if the HDFS cluster uses Kerberos.
However, if a username is specified, then the ticket cache will likely
be required.
Parameters
----------
host : NameNode. Set to "default" for fs.defaultFS from core-site.xml.
port : NameNode's port. Set to 0 for default or logical (HA) nodes.
user : Username when connecting to HDFS; None implies login user.
kerb_ticket : Path to Kerberos ticket cache.
driver : {'libhdfs', 'libhdfs3'}, default 'libhdfs'
Connect using libhdfs (JNI-based) or libhdfs3 (3rd-party C++
library from Apache HAWQ (incubating) )
extra_conf : dict, default None
extra Key/Value pairs for config; Will override any
hdfs-site.xml properties
Notes
-----
The first time you call this method, it will take longer than usual due
to JNI spin-up time.
Returns
-------
filesystem : HadoopFileSystem
"""
fs = HadoopFileSystem(host=host, port=port, user=user,
kerb_ticket=kerb_ticket, driver=driver,
extra_conf=extra_conf)
return fs