def main(argv):
"""
Main method.
This method performs the following tasks:
1. Parse command line arguments
2. Retrieve credentials and connect to Cloudant and WebHDFS
3. Connect to the Cloudant `_changes` feed for checkpointed document
consumption
4. Process each change individually.
5. Upon exception throwing, store the latest checkpoint to local file and
exit.
"""
#add options into the parser
parser = configureOptions()
(options, args) = parser.parse_args()
checkRequiredArguments(options, parser)
print options
# configurations
last_seq = options.last_seq
#get credential
perm_file = '%s/.clou' % os.environ['HOME']
creds = get_creds(perm_file)
#connect to source database
s = Server('https://%s:%s@%s' %
(creds['cloudant_user'], creds['cloudant_pwd'], options.uri))
db = s[options.dbname]
#print db.info()
#connect to target hdfs cluster
hdfs = PyWebHdfsClient(host=options.hdfs_host,
port=options.hdfs_port,
user_name=creds['hdfs_user'])
hdfs.make_dir(options.hdfs_path)
#and here we consume the cloudant `_changes` feed
counter = 0
changestream = ChangesStream(db,
include_docs=True,
heartbeat=True,
since=last_seq)
for c in changestream:
#print c
try:
if counter % 100 == 0:
checkpoint(last_seq)
seq = processChange(hdfs, c, options.hdfs_path)
if seq: # protect against the last line being blank
last_seq = seq
counter += 1
except Exception:
traceback.print_exc()
checkpoint(last_seq)
os._exit(1)
checkpoint(last_seq)
def setup_common_oozie_libs(name_node):
webhdfs_port = '14000'
webhdfs_user = '******'
platform_dir = 'user/deployment/platform'
lib_path_list = ['/usr/hdp/current/hbase-client/lib/hbase-client.jar',
'/usr/hdp/current/hbase-client/lib/hbase-common.jar',
'/usr/hdp/current/hbase-client/lib/hbase-protocol.jar',
'/usr/hdp/current/hbase-client/lib/hbase-server.jar',
'/usr/hdp/current/hbase-client/lib/htrace-core-3.1.0-incubating.jar',
'/usr/hdp/current/hbase-client/lib/hbase-hadoop-compat.jar',
'/usr/hdp/current/hbase-client/lib/hbase-it.jar',
'/usr/hdp/current/hbase-client/lib/hbase-prefix-tree.jar',
'/usr/hdp/current/hbase-client/lib/zookeeper.jar',
'/usr/hdp/current/pig-client/piggybank.jar',
'/usr/hdp/current/spark-client/lib/spark-examples.jar']
# Setup a connection with hdfs using namenode.
hdfs_client = PyWebHdfsClient(host=name_node, port=webhdfs_port, user_name=webhdfs_user, timeout=None)
# Create directory on hadoop file system (HDFS).
hdfs_client.make_dir(platform_dir)
# Creates a new file on HDFS and write contents from local FS.
for path in lib_path_list:
platform_file = '%s/%s' % (platform_dir, os.path.basename(path))
print 'Copying source file: %s to HDFS path %s' % (path, platform_file)
with open(path) as file_data:
try:
hdfs_client.create_file(platform_file, file_data, overwrite=True)
except PyWebHdfsException:
print 'retrying HDFS copy command for %s' % platform_file
time.sleep(5)
hdfs_client.create_file(platform_file, file_data, overwrite=True)
class HDFS(NDArray): ''' HDFS storage Parameters ---------- name : str Name of directory to store text files (Path to the directory) without a leading '/' model : Model If None, the model is taken from the 'with' context vars : list of variables Sampling values will be stored for these variables. If None. 'model.unobserved_RVs' is used host : str The IP address or hostname of the HDFS namenode. By default, it is 'localhost' port : str The port number for WebHDFS on the namenode. By default, it is '50070' user_name : str WebHDFS user_name used for authentication. By default, it is None ''' def __init__(self, name, model=None, vars=None, host='localhost', port='50070', user_name=None): self.hdfs = PyWebHdfsClient(host=host, port=port, user_name=user_name) try: self.hdfs.list_dir(name) except FileNotFound: self.hdfs.make_dir(name) super(HDFS, self).__init__(name, model, vars) def close(self): super(HDFS, self).close() _dump_trace(self.name, self)
def setup_common_oozie_libs(name_node):
webhdfs_port = '14000'
webhdfs_user = '******'
platform_dir = 'user/deployment/platform'
lib_path_list = [
'/opt/cloudera/parcels/CDH/lib/hbase/hbase-client.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/hbase-common.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/hbase-protocol.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/hbase-server.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/lib/htrace-core.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/hbase-hadoop-compat.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/hbase-it.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/hbase-prefix-tree.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/lib/zookeeper.jar',
'/opt/cloudera/parcels/CDH/lib/pig/piggybank.jar'
]
# Setup a connection with hdfs using namenode.
hdfs_client = PyWebHdfsClient(host=name_node,
port=webhdfs_port,
user_name=webhdfs_user,
timeout=None)
# Create directory on hadoop file system (HDFS).
hdfs_client.make_dir(platform_dir)
# Creates a new file on HDFS and write contents from local FS.
for path in lib_path_list:
platform_file = '%s/%s' % (platform_dir, os.path.basename(path))
logging.info('Copying source file: %s to HDFS path %s', path,
platform_file)
with open(path) as file_data:
hdfs_client.create_file(platform_file, file_data, overwrite=True)
def setup_common_oozie_libs(name_node):
webhdfs_port = '14000'
webhdfs_user = '******'
platform_dir = 'user/deployment/platform'
lib_path_list = ['/opt/cloudera/parcels/CDH/lib/hbase/hbase-client.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/hbase-common.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/hbase-protocol.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/hbase-server.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/lib/htrace-core.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/hbase-hadoop-compat.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/hbase-it.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/hbase-prefix-tree.jar',
'/opt/cloudera/parcels/CDH/lib/hbase/lib/zookeeper.jar',
'/opt/cloudera/parcels/CDH/lib/pig/piggybank.jar',
'/opt/cloudera/parcels/CDH/lib/spark/lib/spark-examples.jar']
# Setup a connection with hdfs using namenode.
hdfs_client = PyWebHdfsClient(host=name_node, port=webhdfs_port, user_name=webhdfs_user, timeout=None)
# Create directory on hadoop file system (HDFS).
hdfs_client.make_dir(platform_dir)
# Creates a new file on HDFS and write contents from local FS.
for path in lib_path_list:
platform_file = '%s/%s' % (platform_dir, os.path.basename(path))
logging.info('Copying source file: %s to HDFS path %s', path, platform_file)
with open(path) as file_data:
hdfs_client.create_file(platform_file, file_data, overwrite=True)
class WhenTestingMkdirOperation(unittest.TestCase):
def setUp(self):
self.host = 'hostname'
self.port = '00000'
self.user_name = 'username'
self.webhdfs = PyWebHdfsClient(host=self.host,
port=self.port,
user_name=self.user_name)
self.response = MagicMock()
self.requests = MagicMock(return_value=self.response)
self.path = 'user/hdfs'
self.response = MagicMock()
def test_mkdir_throws_exception_for_not_ok(self):
self.response.status_code = http_client.BAD_REQUEST
self.requests.put.return_value = self.response
with patch('pywebhdfs.webhdfs.requests', self.requests):
with self.assertRaises(errors.PyWebHdfsException):
self.webhdfs.make_dir(self.path)
def test_mkdir_returns_true(self):
self.response.status_code = http_client.OK
self.requests.put.return_value = self.response
with patch('pywebhdfs.webhdfs.requests', self.requests):
result = self.webhdfs.make_dir(self.path)
self.assertTrue(result)
class WhenTestingMkdirOperation(unittest.TestCase):
def setUp(self):
self.host = 'hostname'
self.port = '00000'
self.user_name = 'username'
self.webhdfs = PyWebHdfsClient(host=self.host, port=self.port,
user_name=self.user_name)
self.response = MagicMock()
self.requests = MagicMock(return_value=self.response)
self.path = 'user/hdfs'
self.response = MagicMock()
def test_mkdir_throws_exception_for_not_ok(self):
self.response.status_code = httplib.BAD_REQUEST
self.requests.put.return_value = self.response
with patch('pywebhdfs.webhdfs.requests', self.requests):
with self.assertRaises(errors.PyWebHdfsException):
self.webhdfs.make_dir(self.path)
def test_mkdir_returns_true(self):
self.response.status_code = httplib.OK
self.requests.put.return_value = self.response
with patch('pywebhdfs.webhdfs.requests', self.requests):
result = self.webhdfs.make_dir(self.path)
self.assertTrue(result)
def test_webhdfs_csv(self):
from pywebhdfs.webhdfs import PyWebHdfsClient
dfs = PyWebHdfsClient(host='localhost',port='9870', user_name='hadoop')
dfs.make_dir("/temp")
with open("tests/data/data.csv") as input_file:
dfs.create_file("/temp/data.csv", file_data=input_file, overwrite=True)
dfs.delete_file_dir("/temp", recursive=True)
def main(argv):
"""
Main method.
This method performs the following tasks:
1. Parse command line arguments
2. Retrieve credentials and connect to Cloudant and WebHDFS
3. Connect to the Cloudant `_changes` feed for checkpointed document
consumption
4. Process each change individually.
5. Upon exception throwing, store the latest checkpoint to local file and
exit.
"""
# add options into the parser
parser = configureOptions()
(options, args) = parser.parse_args()
checkRequiredArguments(options, parser)
print options
# configurations
last_seq = options.last_seq
# get credential
perm_file = "%s/.clou" % os.environ["HOME"]
creds = get_creds(perm_file)
# connect to source database
s = Server("https://%s:%s@%s" % (creds["cloudant_user"], creds["cloudant_pwd"], options.uri))
db = s[options.dbname]
# print db.info()
# connect to target hdfs cluster
hdfs = PyWebHdfsClient(host=options.hdfs_host, port=options.hdfs_port, user_name=creds["hdfs_user"])
hdfs.make_dir(options.hdfs_path)
# and here we consume the cloudant `_changes` feed
counter = 0
changestream = ChangesStream(db, include_docs=True, heartbeat=True, since=last_seq)
for c in changestream:
# print c
try:
if counter % 100 == 0:
checkpoint(last_seq)
seq = processChange(hdfs, c, options.hdfs_path)
if seq: # protect against the last line being blank
last_seq = seq
counter += 1
except Exception:
traceback.print_exc()
checkpoint(last_seq)
os._exit(1)
checkpoint(last_seq)
def sharedlib_install(name_node, webhdfs_port, authentic_user, platform_dir,
lib_path_list):
# Setup a connection with hdfs using namenode.
hdfs = PyWebHdfsClient(host=name_node,
port=webhdfs_port,
user_name=authentic_user,
timeout=None)
# Create directory on hadoop file system (HDFS).
hdfs.make_dir(platform_dir)
# Creates a new file on HDFS and write contents from local FS.
for path in lib_path_list:
platform_file = '%s/%s' % (platform_dir, os.path.basename(path))
print >> sys.stdout, 'Copying source file: %s to HDFS path %s' %\
(path, platform_file)
with open(path) as file_data:
hdfs.create_file(platform_file, file_data, overwrite=True)
class Store (store.Store):
"""
HDFS backed store.
"""
def __init__ (self):
""" Connect to store """
self._client = PyWebHdfsClient(host=store_host, port=store_port, user_name=store_user)
def mkdir (self, path):
self._client.make_dir(path)
def read (self, path, open_handle):
return StoreFile(self._client, path, "r", open_handle)
def append (self, path, open_handle):
return StoreFile(self._client, path, "a", open_handle)
def write (self, path, open_handle):
return StoreFile(self._client, path, "w", open_handle)
def exists (self, path):
try:
dirinfo = self._client.list_dir(path)
return True
except errors.FileNotFound:
return False
def walk (self, path, visitor, recursive = False):
""" Walk files in a path. Use recursive=True to include subdirs """
dirinfo = self._client.list_dir(path)
for status in dirinfo["FileStatuses"]["FileStatus"]:
if recursive and status["type"] == "DIRECTORY":
if len(path) > 0:
self.walk(path + "/" + status["pathSuffix"], visitor, recursive)
else:
self.walk(status["pathSuffix"], visitor, recursive)
else:
info = dict(name=status["pathSuffix"],
modify=datetime.fromtimestamp(status["modificationTime"]),
size=status["length"])
visitor(path, info)
class HDFS(NDArray):
'''
HDFS storage
Parameters
----------
name : str
Name of directory to store text files (Path to the directory) without
a leading '/'
model : Model
If None, the model is taken from the 'with' context
vars : list of variables
Sampling values will be stored for these variables. If None.
'model.unobserved_RVs' is used
host : str
The IP address or hostname of the HDFS namenode. By default,
it is 'localhost'
port : str
The port number for WebHDFS on the namenode. By default, it
is '50070'
user_name : str
WebHDFS user_name used for authentication. By default, it is
None
'''
def __init__(self,
name,
model=None,
vars=None,
host='localhost',
port='50070',
user_name=None):
self.hdfs = PyWebHdfsClient(host=host, port=port, user_name=user_name)
try:
self.hdfs.list_dir(name)
except FileNotFound:
self.hdfs.make_dir(name)
super(HDFS, self).__init__(name, model, vars)
def close(self):
super(HDFS, self).close()
_dump_trace(self.name, self)
def setup_common_oozie_libs(name_node):
webhdfs_port = '14000'
webhdfs_user = '******'
platform_dir = 'user/deployment/platform'
lib_path_list = [
'/usr/hdp/current/hbase-client/lib/hbase-client.jar',
'/usr/hdp/current/hbase-client/lib/hbase-common.jar',
'/usr/hdp/current/hbase-client/lib/hbase-protocol.jar',
'/usr/hdp/current/hbase-client/lib/hbase-server.jar',
'/usr/hdp/current/hbase-client/lib/htrace-core-3.1.0-incubating.jar',
'/usr/hdp/current/hbase-client/lib/hbase-hadoop-compat.jar',
'/usr/hdp/current/hbase-client/lib/hbase-it.jar',
'/usr/hdp/current/hbase-client/lib/hbase-prefix-tree.jar',
'/usr/hdp/current/hbase-client/lib/zookeeper.jar',
'/usr/hdp/current/pig-client/piggybank.jar',
'/usr/hdp/current/spark-client/lib/spark-examples.jar'
]
# Setup a connection with hdfs using namenode.
hdfs_client = PyWebHdfsClient(host=name_node,
port=webhdfs_port,
user_name=webhdfs_user,
timeout=None)
# Create directory on hadoop file system (HDFS).
hdfs_client.make_dir(platform_dir)
# Creates a new file on HDFS and write contents from local FS.
for path in lib_path_list:
platform_file = '%s/%s' % (platform_dir, os.path.basename(path))
print 'Copying source file: %s to HDFS path %s' % (path, platform_file)
with open(path) as file_data:
try:
hdfs_client.create_file(platform_file,
file_data,
overwrite=True)
except PyWebHdfsException:
print 'retrying HDFS copy command for %s' % platform_file
time.sleep(5)
hdfs_client.create_file(platform_file,
file_data,
overwrite=True)
#1 imports
from pywebhdfs.webhdfs import PyWebHdfsClient
#2 make connection with hadoop file system
hdfs = PyWebHdfsClient(user_name="hdfs",port=50070,host="sandbox.hortonworks.com")
hdfs.delete_file_dir('chapter5/LoanStats3d.csv',recursive=True)
#4 recreate the chapters directory
hdfs.make_dir('chapter5')
#5 upload the csv file
with open('./data/stored_csv.csv') as file_data:
hdfs.create_file('chapter5/LoanStats3d.csv',file_data, overwrite=True)
#6 print the status to see if this succeeded.
print hdfs.get_file_dir_status('chapter5/LoanStats3d.csv')
class HDFS(object):
def __init__(self, host, port, user):
self._hdfs = PyWebHdfsClient(host=host,
port=port,
user_name=user,
timeout=None)
logging.debug('webhdfs = %s@%s:%s', user, host, port)
def recursive_copy(self,
local_path,
remote_path,
exclude=None,
permission=755):
if exclude is None:
exclude = []
c_path = canonicalize(remote_path)
logging.debug('making %s', c_path)
self._hdfs.make_dir(c_path, permission=permission)
fs_g = os.walk(local_path)
for dpath, dnames, fnames in fs_g:
_, relative_path = dpath.split(local_path)
for dname in dnames:
if dname not in exclude:
c_path = canonicalize('%s/%s/%s' %
(remote_path, relative_path, dname))
logging.debug('making %s', c_path)
self._hdfs.make_dir(c_path, permission=permission)
for fname in fnames:
if fname not in exclude:
data = file(
canonicalize('%s/%s/%s' %
(local_path, relative_path, fname)), 'rb')
c_path = canonicalize('%s/%s/%s' %
(remote_path, relative_path, fname))
logging.debug('creating %s', c_path)
self._hdfs.create_file(c_path,
data,
overwrite=True,
permission=permission)
data.close()
def make_dir(self, path, permission=755):
logging.debug('make_dir: %s', path)
self._hdfs.make_dir(canonicalize(path), permission=permission)
def create_file(self, data, remote_file_path, permission=755):
logging.debug('create_file: %s', remote_file_path)
sio = BytesIO(data)
self._hdfs.create_file(canonicalize(remote_file_path),
sio,
overwrite=True,
permission=permission)
def append_file(self, data, remote_file_path):
logging.debug('append to: %s', remote_file_path)
self._hdfs.append_file(canonicalize(remote_file_path), data)
def stream_file_to_disk(self, remote_file_path, local_file_path):
chunk_size = 10 * 1024 * 1024
offset = 0
with open(local_file_path, 'wb') as dest_file:
data = self._hdfs.read_file(canonicalize(remote_file_path),
offset=offset,
length=chunk_size)
while True:
dest_file.write(data)
if len(data) < chunk_size:
break
offset += chunk_size
data = self._hdfs.read_file(canonicalize(remote_file_path),
offset=offset,
length=chunk_size)
def read_file(self, remote_file_path):
data = self._hdfs.read_file(canonicalize(remote_file_path))
return data
def remove(self, path, recursive=False):
logging.debug('remove: %s', path)
self._hdfs.delete_file_dir(canonicalize(path), recursive)
def file_exists(self, path):
try:
self._hdfs.get_file_dir_status(path)
return True
except:
return False
import requests
source = requests.get("https://resources.lendingclub.com/LoanStats3d.csv.zip",
verify=False)
stringio = StringIO.StringIO(source.content)
unzipped = zipfile.ZipFile(stringio)
import pandas as pd
from pywebhdfs.webhdfs import PyWebHdfsClient
subselection_csv = pd.read_csv(unzipped.open('LoanStats3d.csv'),
skiprows=1,
skipfooter=2,
engine='python')
stored_csv = subselection_csv.to_csv('./stored_csv.csv')
hdfs = PyWebHdfsClient(user_name="hdfs", port=50070, host="sandbox")
hdfs.make_dir('chapter5')
with open('./stored_csv.csv') as file_data:
hdfs.create_file('chapter5/LoanStats3d.csv', file_data, overwrite=True)
print(hdfs.get_file_dir_status('chapter5/LoanStats3d.csv'))
from pyspark.sql import HiveContext
# sc = SparkContext()
sqlContext = HiveContext(sc)
data = sc.textFile("/chapter5/LoanStats3d.csv")
parts = data.map(lambda r: r.split(','))
firstline = parts.first()
datalines = parts.filter(lambda x: x != firstline)
def cleans(row):
class MulticlassLogisticRegressionModelTrainer(object):
pass
def __init__(self):
pass
def hdfsizePath(self, path):
return self.hdfsServerUrl+path
def start(self,q,parentEnv, configJsonStr):
pass
self.config = DictionaryAsNestedObjectSerializer(json.loads(configJsonStr))
self.hdfs = PyWebHdfsClient(host=self.config.acm.servers.hdfs.host,port=self.config.acm.servers.hdfs.restPort, user_name=self.config.acm.servers.hdfs.fileOwner)
self.hdfsServerUrl = "hdfs://"+self.config.acm.servers.hdfs.host+":"+str(self.config.acm.servers.hdfs.port)
env_ = json.loads(parentEnv)
py4jExists=False
for key in env_.keys():
os.environ[key]=env_[key]
if "py4j-" in env_[key]:
py4jExists=True
### set pyspark env variable ###
#os.environ["SPARK_HOME"]="/home/halil/programs/spark230"
#if os.environ.get("PYTHONPATH") is None:
# os.environ["PYTHONPATH"] = os.path.join(os.environ["SPARK_HOME"], "python/")
#
#if py4jExists==False:
# os.environ["PYTHONPATH"] = os.path.join(os.environ["SPARK_HOME"], "python/lib/py4j-0.10.6-src.zip")+ ":"+ os.environ["PYTHONPATH"]
#set config
trainDataFiles= self.hdfsizePath(self.config.acm.models.classification.data.hdfs.inputDir+"/*.csv")
print (trainDataFiles)
sc =SparkContext()
sqlContext = SQLContext(sc)
data = sqlContext.read.format('com.databricks.spark.csv').options(header='true', inferschema='true').load(trainDataFiles).limit(1000)
print(data.columns)
drop_list = ['Dates', 'DayOfWeek', 'PdDistrict', 'Resolution', 'Address', 'X', 'Y']
data = data.select([column for column in data.columns if column not in drop_list])
data.show(5)
data.printSchema()
# by top 20 categories
data.groupBy("Category") \
.count() \
.orderBy(col("count").desc()) \
.show()
# by top 20 descriptions
data.groupBy("Descript") \
.count() \
.orderBy(col("count").desc()) \
.show()
# regular expression tokenizer
regexTokenizer = RegexTokenizer(inputCol="Descript", outputCol="words", pattern="\\W")
# stop words
add_stopwords = ["http","https","amp","rt","t","c","the"] # standard stop words
stopwordsRemover = StopWordsRemover(inputCol="words", outputCol="filtered").setStopWords(add_stopwords)
# bag of words count
countVectors = CountVectorizer(inputCol="filtered", outputCol="features", vocabSize=10000, minDF=5)
label_stringIdx = StringIndexer(inputCol = "Category", outputCol = "label")
transformers=[regexTokenizer, stopwordsRemover, countVectors, label_stringIdx]
pipeline = Pipeline(stages=transformers)
pipelineFit = pipeline.fit(data)
dataset = pipelineFit.transform(data)
dataset.show(5)
### Randomly split data into training and test sets. set seed for reproducibility
(trainingData, testData) = dataset.randomSplit([0.7, 0.3], seed = 100)
print("Training Dataset Count: " + str(trainingData.count()))
print("Test Dataset Count: " + str(testData.count()))
# Build the model
lr = LogisticRegression(maxIter=20, regParam=0.3, elasticNetParam=0)
# Train model with Training Data
lrModel = lr.fit(trainingData)
savedModelsDir=self.hdfsizePath(self.config.acm.models.classification.data.hdfs.savedModels)
savedModelsZipDir=self.hdfsizePath(self.config.acm.models.classification.data.hdfs.zipDir)
modelSavePolicy=self.config.acm.models.classification.modelSavePolicy
if modelSavePolicy=="mostRecentOne":
time_ms = str(int(time.time()*1000))
#if not os.path.exists(outputDir):
# os.mkdir(outputDir)
#if not os.path.exists(zipDir):
# os.mkdir(zipDir)
self.hdfs.make_dir(self.config.acm.models.classification.data.hdfs.savedModels)
self.hdfs.make_dir(self.config.acm.models.classification.data.hdfs.zipDir)
newModelDirName = self.config.acm.models.classification.data.hdfs.savedModels + "/" + time_ms
modelOutputPath = newModelDirName+"/model"
pipelineOutputPath = newModelDirName+"/pipeline"
self.hdfs.make_dir(newModelDirName)
self.hdfs.make_dir(modelOutputPath)
self.hdfs.make_dir(pipelineOutputPath)
lrModel.write().overwrite().save(self.hdfsizePath( modelOutputPath))
pipelineFit.write().overwrite().save(self.hdfsizePath(pipelineOutputPath))
class HDFS(object):
def __init__(self, host, port, user):
self._hdfs = PyWebHdfsClient(
host=host, port=port, user_name=user, timeout=None)
logging.debug('webhdfs = %s@%s:%s', user, host, port)
def recursive_copy(self, local_path, remote_path, exclude=None):
if exclude is None:
exclude = []
c_path = canonicalize(remote_path)
logging.debug('making %s', c_path)
self._hdfs.make_dir(c_path)
fs_g = os.walk(local_path)
for dpath, dnames, fnames in fs_g:
_, relative_path = dpath.split(local_path)
for dname in dnames:
if dname not in exclude:
c_path = canonicalize(
'%s/%s/%s' %
(remote_path, relative_path, dname))
logging.debug('making %s', c_path)
self._hdfs.make_dir(c_path)
for fname in fnames:
if fname not in exclude:
data = file(
canonicalize(
'%s/%s/%s' %
(local_path, relative_path, fname)), 'rb')
c_path = canonicalize(
'%s/%s/%s' %
(remote_path, relative_path, fname))
logging.debug('creating %s', c_path)
self._hdfs.create_file(c_path, data, overwrite=True)
data.close()
def make_dir(self, path):
logging.debug('make_dir: %s', path)
self._hdfs.make_dir(canonicalize(path))
def create_file(self, data, remote_file_path):
logging.debug('create_file: %s', remote_file_path)
sio = StringIO.StringIO(data)
self._hdfs.create_file(
canonicalize(remote_file_path),
sio,
overwrite=True)
def append_file(self, data, remote_file_path):
logging.debug('append to: %s', remote_file_path)
self._hdfs.append_file(canonicalize(remote_file_path), data)
def stream_file_to_disk(self, remote_file_path, local_file_path):
chunk_size = 10*1024*1024
offset = 0
with open(local_file_path, 'wb') as dest_file:
data = self._hdfs.read_file(canonicalize(remote_file_path), offset=offset, length=chunk_size)
while True:
dest_file.write(data)
if len(data) < chunk_size:
break
offset += chunk_size
data = self._hdfs.read_file(canonicalize(remote_file_path), offset=offset, length=chunk_size)
def read_file(self, remote_file_path):
data = self._hdfs.read_file(canonicalize(remote_file_path))
return data
def remove(self, path, recursive=False):
logging.debug('remove: %s', path)
self._hdfs.delete_file_dir(canonicalize(path), recursive)
def hdfsPutTrainDataToDir(filePath, dir_):
fname = os.path.basename(filePath)
hdfsPut(filePath, dir_ + "/" + fname)
conf = SparkConf()
conf.setMaster("spark://acm-spark-master:7077")
conf.setAppName("batch-multiclass-text-classification")
sc = SparkContext()
sqlContext = SQLContext(sc)
trainDataFile = "./data/sanfrancisco-crime/train.csv"
hdfsPath = "/acm/ml/clsf/data/test001"
modelsPath = hdfsPath + "/models"
hdfs.make_dir(hdfsPath)
hdfs.make_dir(modelsPath)
hdfsPutTrainDataToDir(trainDataFile, hdfsPath)
data = sqlContext.read.format('com.databricks.spark.csv').options(
header='true',
inferschema='true').load("hdfs://namenode:9000/" + hdfsPath).limit(1000)
print(data.columns)
drop_list = [
'Dates', 'DayOfWeek', 'PdDistrict', 'Resolution', 'Address', 'X', 'Y'
]
data = data.select(
[column for column in data.columns if column not in drop_list])
data.show(5)
_LOG = logging.getLogger(__name__)
example_dir = 'user/hdfs/example_dir'
example_file = '{dir}/example.txt'.format(dir=example_dir)
example_data = '01010101010101010101010101010101010101010101\n'
rename_dir = 'user/hdfs/example_rename'
# create a new client instance
hdfs = PyWebHdfsClient(host='localhost', port='50070',
user_name='hduser')
# create a new directory for the example
print('making new HDFS directory at: {0}\n'.format(example_dir))
hdfs.make_dir(example_dir)
# get a dictionary of the directory's status
dir_status = hdfs.get_file_dir_status(example_dir)
print(dir_status)
# create a new file on hdfs
print('making new file at: {0}\n'.format(example_file))
hdfs.create_file(example_file, example_data)
file_status = hdfs.get_file_dir_status(example_file)
print(file_status)
# get the checksum for the file
file_checksum = hdfs.get_file_checksum(example_file)
print(file_checksum)
#!/usr/bin/env python
from pywebhdfs.webhdfs import PyWebHdfsClient
import os
hdfs = PyWebHdfsClient(host='namenode',port='50070', user_name='root')
def hdfsPut(local_path, hdfs_path):
with open(local_path) as file_data:
hdfs.create_file(hdfs_path, file_data=file_data, overwrite=True)
def hdfsPutTrainDataToDir(filePath, dir_):
fname= os.path.basename(filePath)
hdfsPath = dir_+"/"+fname
hdfsPut(filePath, hdfsPath)
trainDataFile="./data/sanfrancisco-crime/train.csv"
hdfsPath="/acm/ml/clsf/data/test001"
hdfs.make_dir(hdfsPath)
hdfsPutTrainDataToDir(trainDataFile,hdfsPath)
def upload_to_hdfs(self, local_file, table, index):
'''
upload file from local filesystem to hdfs
'''
hiveOper = hive_op.HiveOperation()
local_dir = self._conf.get('local', 'data_dir')
local_path = '{}{}/{}'.format(local_dir, index, local_file)
host1 = self._conf.get('hdfs', 'name_node1')
host2 = self._conf.get('hdfs', 'name_node2')
user = self._conf.get('hdfs', 'user')
port = self._conf.getint('hdfs', 'port')
hdfs_base_path = self._conf.get('hdfs', 'upload_path')
hdfs_dir_path = '{}{}'.format(hdfs_base_path, index)
hdfs_path = '{}{}/{}'.format(hdfs_base_path, index, local_file)
#implement HA manually
try:
hdfs_cli = PyWebHdfsClient(host=host1, port=port, user_name=user)
hdfs_cli.list_dir('/')
except Exception as e:
logger.warn('open hdfs client failed error {}'.format(e))
hdfs_cli = PyWebHdfsClient(host=host2, port=port, user_name=user)
hdfs_cli.list_dir('/')
if hdfs_cli is None:
logger.error('no active host')
return None
try:
hdfs_cli.get_file_dir_status(hdfs_path)
# 若hdfs中临时文件存在，表示可能是上次上传hive失败，或者进程中途被杀导致
# 先将临时文件中的数据导入hive，再进行下一步操作
ret = hiveOper.load_hdfs_file_into_tmp_table(hdfs_path, table)
if ret == -1:
logger.error('load from hdfs to tmp table failed')
logger.info('last time! {} load into tmp finished'.format(table))
hiveOper.load_tmp_table_to_main(table)
logger.info(
'last time! {} load tmp table to main finished'.format(table))
#FileNotFountException
except Exception as e:
#文件不存在是正常情况
logger.debug('no such file {}'.format(hdfs_path))
retry_count = 0
upload_finished = False
while retry_count <= 10 and not upload_finished:
with open(local_path) as f:
logger.debug('''local path is {}, hdfs_cli is {},
file is {}, hdfs_path is {}'''.format(
local_path, hdfs_cli, f, hdfs_path))
#hdfs_cli.delete_file_dir(hdfs_path)
#若目录不存在，先创建目录
try:
hdfs_cli.get_file_dir_status(hdfs_dir_path)
except Exception as e:
hdfs_cli.make_dir(hdfs_dir_path)
try:
hdfs_cli.create_file(hdfs_path, f)
upload_finished = True
except Exception as e:
logger.warn('''create file on hdfs failed,
local path is {}, hdfs path is {},
retry count {}, upload flag {}'''.format(
local_path, hdfs_path, retry_count, upload_finished))
logger.warn('error is {}'.format(e))
retry_count += 1
if retry_count <= 10:
return hdfs_path
else:
logger.error('''{} upload 10 times, still failed,
retry count {}, upload_flag is {}'''.format(
local_path, retry_count, upload_finished))
return None
class HadoopFileSystem(BaseFs.FileSystem):
def __init__(self,
vcPath,
simulateOnly=False,
isVerbose=False,
logger=None,
user=None,
host=None,
port=None):
BaseFs.FileSystem.__init__(self, simulateOnly, isVerbose, logger)
config = Config.Config()
hdfsUser, hdfsHost, hdfsPort = config.getHadoopConfig(user, host, port)
self.hdfs = PyWebHdfsClient(host=hdfsHost,
port=hdfsPort,
user_name=hdfsUser)
self.vcPath = vcPath
def make_fd(self, path, isSrc, dstDirMustExist):
fd = None
try:
fd = HadoopFileDescriptor(self, path, isSrc, dstDirMustExist)
except pywebhdfs.errors.FileNotFound:
self.logger.info("DESC: does not exist: " + path)
raise Errors.FileNotFound("Path {0} does not exist".format(path))
except pywebhdfs.errors.Unauthorized as e:
self.logger.info("Unauthorized for path {0}: {1}".format(path, e))
raise Errors.Unauthorized(
"Unauthorized access to the path {0}: {1}".format(path, e))
except requests.exceptions.RequestException as e:
self.logger.info("ConnectionError for path {0}: {1}".format(
path, e))
raise Errors.BadConnection(
"Connection error while looking for path: {0}, exc={1}".format(
path, e))
except pywebhdfs.errors.PyWebHdfsException as e:
self.logger.info("PyWebHdfsException for path {0}: {1}".format(
path, e))
raise Errors.FsException(
"An exception happened while looking for path: {0}, exc={1}".
format(path, e))
return fd
def exists_file_dir(self, fd):
try:
return self.hdfs.exists_file_dir(fd.abspath)
except pywebhdfs.errors.Unauthorized as e:
self.logger.info("Unauthorized for path {0}: {1}".format(
fd.abspath, e))
raise Errors.Unauthorized(
"Unauthorized access to the path {0}: {1}".format(
fd.abspath, e))
except requests.exceptions.RequestException as e:
self.logger.info("ConnectionError for path {0}: {1}".format(
fd.abspath, e))
raise Errors.BadConnection(
"Connection error during HDFS exists test: {0}, exc={1}".
format(fd.abspath, e))
except pywebhdfs.errors.PyWebHdfsException as e:
self.logger.info("PyWebHdfsException for path {0}: {1}".format(
fd.abspath, e))
raise Errors.FsException(
"An exception happened during HDFS exists test: {0}, exc={1}".
format(fd.abspath, e))
def delete_file_dir(self, fd, recursive=False, force=False):
if self.simulateOnly:
print("SIMULATE -> remove file/dir: {0}, recursive={1}".format(
fd.abspath, recursive))
else:
try:
if not recursive or force or \
query_yes_no(question="Are you sure you want to delete folder recursively?", default="no"):
status = self.hdfs.delete_file_dir(fd.abspath,
recursive=recursive)
except pywebhdfs.errors.Unauthorized as e:
self.logger.info("Unauthorized for path {0}: {1}".format(
fd.abspath, e))
raise Errors.Unauthorized(
"Unauthorized access to the path {0}: {1}".format(
fd.abspath, e))
except requests.exceptions.RequestException as e:
self.logger.info("ConnectionError for path {0}: {1}".format(
fd.abspath, e))
raise Errors.BadConnection(
"Connection error during HDFS delete directory: {0}, exc={1}"
.format(fd.abspath, e))
except pywebhdfs.errors.PyWebHdfsException as e:
self.logger.info("PyWebHdfsException for path {0}: {1}".format(
fd.abspath, e))
raise Errors.FsException(
"An exception happened during HDFS delete directory: {0}, exc={1}"
.format(fd.abspath, e))
def list_dir(self, fd):
try:
status = self.hdfs.list_dir(fd.abspath)
except pywebhdfs.errors.Unauthorized as e:
self.logger.info("Unauthorized for path {0}: {1}".format(
fd.abspath, e))
raise Errors.Unauthorized(
"Unauthorized access to the path {0}: {1}".format(
fd.abspath, e))
except requests.exceptions.RequestException as e:
self.logger.info("ConnectionError for path {0}: {1}".format(
fd.abspath, e))
raise Errors.BadConnection(
"Connection error while looking for path: {0}, exc={1}".format(
fd.abspath, e))
except pywebhdfs.errors.PyWebHdfsException as e:
self.logger.info("PyWebHdfsException for path {0}: {1}".format(
fd.abspath, e))
raise Errors.FsException(
"An exception happened while looking for path: {0}, exc={1}".
format(fd.abspath, e))
currentDir = status["FileStatuses"]["FileStatus"]
for item in currentDir:
yield HadoopFileDescriptor(self,
fd.abspath,
isSrc=True,
needsDstDirCheck=False,
fileJson=item)
def make_dir(self, path):
if self.simulateOnly:
print("SIMULATE -> make dir: " + path)
else:
try:
self.hdfs.make_dir(path)
except pywebhdfs.errors.Unauthorized as e:
self.logger.info("Unauthorized for path {0}: {1}".format(
path, e))
raise Errors.Unauthorized(
"Unauthorized access to the path {0}: {1}".format(path, e))
except requests.exceptions.RequestException as e:
self.logger.info("ConnectionError for path {0}: {1}".format(
path, e))
raise Errors.BadConnection(
"Connection error during HDFS create directory: {0}, exc={1}"
.format(path, e))
except pywebhdfs.errors.PyWebHdfsException as e:
self.logger.info("PyWebHdfsException for path {0}: {1}".format(
path, e))
raise Errors.FsException(
"An exception happened during HDFS create directory: {0}, exc={1}"
.format(path, e))
def open_file(self, fd, rwMode):
return fd
def close_file(self, fd):
pass
def touch_file(self, fd):
if self.simulateOnly:
print("SIMULATE -> touch file: " + fd.abspath)
else:
try:
self.hdfs.create_file(fd.abspath, 0, overwrite=True)
except pywebhdfs.errors.Unauthorized as e:
self.logger.info("Unauthorized for path {0}: {1}".format(
fd.abspath, e))
raise Errors.Unauthorized(
"Unauthorized access to the path {0}: {1}".format(
fd.abspath, e))
except requests.exceptions.RequestException as e:
self.logger.info("ConnectionError for path {0}: {1}".format(
fd.abspath, e))
raise Errors.BadConnection(
"Connection error during HDFS create file: {0}, exc={1}".
format(fd.abspath, e))
except pywebhdfs.errors.PyWebHdfsException as e:
self.logger.info("PyWebHdfsException for path {0}: {1}".format(
fd.abspath, e))
raise Errors.FsException(
"An exception happened during HDFS create file: {0}, exc={1}"
.format(fd.abspath, e))
def truncate_file(self, fd, size):
if self.simulateOnly:
print("SIMULATE -> truncate file: {0}, size={1}".format(
fd.abspath, size))
else:
try:
self.hdfs.truncate_file(fd.abspath, size)
except pywebhdfs.errors.Unauthorized as e:
self.logger.info("Unauthorized for path {0}: {1}".format(
fd.abspath, e))
raise Errors.Unauthorized(
"Unauthorized access to the path {0}: {1}".format(
fd.abspath, e))
except requests.exceptions.RequestException as e:
self.logger.info("ConnectionError for path {0}: {1}".format(
fd.abspath, e))
raise Errors.BadConnection(
"Connection error during HDFS truncate file: {0}, exc={1}".
format(fd.abspath, e))
except pywebhdfs.errors.PyWebHdfsException as e:
self.logger.info("PyWebHdfsException for path {0}: {1}".format(
fd.abspath, e))
raise Errors.FsException(
"An exception happened during HDFS truncate file: {0}, exc={1}"
.format(fd.abspath, e))
def try_concat_files(self, fd, chunkFdList):
# Workaround for unordered concat bug in Hadoop 2.7.1 is to use one source at the time
# https://issues.apache.org/jira/browse/HDFS-8891
currIndex = 0
concatStep = 20
chunkedList = [
chunkFdList[pos:pos + concatStep]
for pos in range(0, len(chunkFdList), concatStep)
]
for sourceChunk in chunkedList:
try:
self.concat_files(fd, sourceChunk)
currIndex += len(sourceChunk)
except Errors.FsException as e:
break
return currIndex
def concat_files(self, fd, chunkFdList):
strList = list()
for chunkFd in chunkFdList:
strList.append(chunkFd.abspath)
if self.simulateOnly:
print("SIMULATE -> concat file: {0}, sources={1}".format(
fd.abspath, ",".join(strList)))
else:
try:
self.hdfs.concat_files(fd.abspath, strList)
except pywebhdfs.errors.Unauthorized as e:
self.logger.info("Unauthorized for path {0}: {1}".format(
fd.abspath, e))
raise Errors.Unauthorized(
"Unauthorized access to the path {0}: {1}".format(
fd.abspath, e))
except requests.exceptions.RequestException as e:
self.logger.info("ConnectionError for path {0}: {1}".format(
fd.abspath, e))
raise Errors.BadConnection(
"Connection error during HDFS concat file: {0}, exc={1}".
format(fd.abspath, e))
except pywebhdfs.errors.PyWebHdfsException as e:
self.logger.info("PyWebHdfsException for path {0}: {1}".format(
fd.abspath, e))
raise Errors.FsException(
"An exception happened during HDFS concat file: {0}, exc={1}"
.format(fd.abspath, e))
def read_data(self, fd, offset, size):
if offset >= fd.size:
return ""
else:
try:
contents = self.hdfs.read_file(fd.abspath,
offset=offset,
length=size)
except pywebhdfs.errors.Unauthorized as e:
self.logger.info("Unauthorized for path {0}: {1}".format(
fd.abspath, e))
raise Errors.Unauthorized(
"Unauthorized access to the path {0}: {1}".format(
fd.abspath, e))
except requests.exceptions.RequestException as e:
self.logger.info("ConnectionError for path {0}: {1}".format(
fd.abspath, e))
raise Errors.BadConnection(
"Connection error during HDFS read file: {0}, exc={1}".
format(fd.abspath, e))
except pywebhdfs.errors.PyWebHdfsException as e:
self.logger.info("PyWebHdfsException for path {0}: {1}".format(
fd.abspath, e))
raise Errors.FsException(
"An exception happened during HDFS read file: {0}, exc={1}"
.format(fd.abspath, e))
return contents
def append_data(self, fd, data):
if self.simulateOnly:
print("SIMULATE -> write file data: " + fd.abspath)
else:
try:
self.hdfs.append_file(fd.abspath, data)
except pywebhdfs.errors.Unauthorized as e:
self.logger.info("Unauthorized for path {0}: {1}".format(
fd.abspath, e))
raise Errors.Unauthorized(
"Unauthorized access to the path {0}: {1}".format(
fd.abspath, e))
except requests.exceptions.RequestException as e:
self.logger.info("ConnectionError for path {0}: {1}".format(
fd.abspath, e))
raise Errors.BadConnection(
"Connection error during HDFS append file: {0}, exc={1}".
format(fd.abspath, e))
except pywebhdfs.errors.PyWebHdfsException as e:
self.logger.info("PyWebHdfsException for path {0}: {1}".format(
fd.abspath, e))
raise Errors.FsException(
"An exception happened during HDFS append file: {0}, exc={1}"
.format(fd.abspath, e))
def local_mv_file(self, src, dst):
if self.simulateOnly:
print("SIMULATE -> local move file: {0} -> {1} ".format(
src.abspath, dst.abspath))
else:
try:
self.hdfs.rename_file_dir(src.abspath, dst.abspath)
except pywebhdfs.errors.Unauthorized as e:
self.logger.info("Unauthorized for path {0}: {1}".format(
src.abspath, e))
raise Errors.Unauthorized(
"Unauthorized access to the path {0}: {1}".format(
src.abspath, e))
except requests.exceptions.RequestException as e:
self.logger.info("ConnectionError for path {0}: {1}".format(
src.abspath, e))
raise Errors.BadConnection(
"Connection error during HDFS rename file: {0}, exc={1}".
format(src.abspath, e))
except pywebhdfs.errors.PyWebHdfsException as e:
self.logger.info("PyWebHdfsException for path {0}: {1}".format(
src.abspath, e))
raise Errors.FsException(
"An exception happened during HDFS rename file: {0}, exc={1}"
.format(src.abspath, e))
def local_cp_file(self, src, dst):
# This is an open issue in Hadoop community: https://issues.apache.org/jira/browse/HDFS-3370
# Instead, we can do a symbolic link
if self.simulateOnly:
print("SIMULATE -> local copy file: {0} -> {1} ".format(
src.abspath, dst.abspath))
else:
print(
"Copy within HDFS is not supported due to lack of Hadoop support"
)
print(
"Once symbolic links are enabled, this feature will be enabled"
)
sys.exit(1)
# self.hdfs.create_sym_link(src.abspath, dst.abspath, createParent=True)
def get_hdfs_file_dir_json(self, path):
try:
status = self.hdfs.get_file_dir_status(path)
return status["FileStatus"]
except pywebhdfs.errors.FileNotFound:
return None
def validate_hdfs_arg(self, arg):
if not arg.startswith(self.vcPath):
print("Error: You don't have permissions to the path: %s" % arg)
print("Your path must be rooted under: %s" % self.vcPath)
sys.exit(1)
def save(self):
hdfs = PyWebHdfsClient(host=os.environ["WEBHDFS_HOST"], port='14000', user_name='oozie')
coordinator_path = "{0}/{1}/coordinator.xml".format(self.path, self.name)
hdfs.make_dir(self.path)
hdfs.create_file(coordinator_path, self.as_xml())
import logging
logging.basicConfig(level=logging.DEBUG)
_LOG = logging.getLogger(__name__)
example_dir = 'user/hdfs/example_dir'
example_file = '{dir}/example.txt'.format(dir=example_dir)
example_data = '01010101010101010101010101010101010101010101\n'
rename_dir = 'user/hdfs/example_rename'
# create a new client instance
hdfs = PyWebHdfsClient(host='localhost', port='50070', user_name='hduser')
# create a new directory for the example
print('making new HDFS directory at: {0}\n'.format(example_dir))
hdfs.make_dir(example_dir)
# get a dictionary of the directory's status
dir_status = hdfs.get_file_dir_status(example_dir)
print dir_status
# create a new file on hdfs
print('making new file at: {0}\n'.format(example_file))
hdfs.create_file(example_file, example_data)
file_status = hdfs.get_file_dir_status(example_file)
print file_status
# append to the file created in previous step
print('appending to file at: {0}\n'.format(example_file))
hdfs.append_file(example_file, example_data)
def save(self, workflow_name="workflow.xml"):
hdfs = PyWebHdfsClient(host=os.environ["WEBHDFS_HOST"], port='14000', user_name='oozie')
workflow_path = "{0}/{1}/workflow.xml".format(self.path, self.name)
hdfs.make_dir(self.path)
hdfs.create_file(workflow_path, self.as_xml())