def chainMergeNM(self, lNM=None, lNMJvm=None, lShuffle=None):
'''
:return: -> merged namemanager metrics
'''
# Read files
if lNM is None and lNMJvm is None and lShuffle is None:
allNM = glob.glob(os.path.join(self.dataDir, "NM_*.csv"))
allNMJvm = glob.glob(os.path.join(self.dataDir, "JVM_NM_*.csv"))
allShuffle = glob.glob(os.path.join(self.dataDir, "Shuffle_*.csv"))
else:
allNM =lNM
allNMJvm = lNMJvm
allShuffle = lShuffle
# Get column headers and gen dict with new col headers
colNamesNM = csvheaders2colNames(allNM[0], 'slave1')
df_NM = self.chainMerge(allNM, colNamesNM, iterStart=2)
colNamesJVMNM = csvheaders2colNames(allNMJvm[0], 'slave1')
df_NM_JVM = self.chainMerge(allNMJvm, colNamesJVMNM, iterStart=2)
colNamesShuffle = csvheaders2colNames(allShuffle[0], 'slave1')
df_Shuffle = self.chainMerge(allShuffle, colNamesShuffle, iterStart=2)
return df_NM, df_NM_JVM, df_Shuffle
def chainMergeNM(self, lNM=None, lNMJvm=None, lShuffle=None):
'''
:return: -> merged namemanager metrics
'''
# Read files
if lNM is None and lNMJvm is None and lShuffle is None:
allNM = glob.glob(os.path.join(self.dataDir, "NM_*.csv"))
allNMJvm = glob.glob(os.path.join(self.dataDir, "JVM_NM_*.csv"))
allShuffle = glob.glob(os.path.join(self.dataDir, "Shuffle_*.csv"))
else:
allNM =lNM
allNMJvm = lNMJvm
allShuffle = lShuffle
# Get column headers and gen dict with new col headers
colNamesNM = csvheaders2colNames(allNM[0], 'slave1')
df_NM = self.chainMerge(allNM, colNamesNM, iterStart=2)
colNamesJVMNM = csvheaders2colNames(allNMJvm[0], 'slave1')
df_NM_JVM = self.chainMerge(allNMJvm, colNamesJVMNM, iterStart=2)
colNamesShuffle = csvheaders2colNames(allShuffle[0], 'slave1')
df_Shuffle = self.chainMerge(allShuffle, colNamesShuffle, iterStart=2)
return df_NM, df_NM_JVM, df_Shuffle
def chainMergeMongoDB(self, lmongo):
'''
:param lmongo: -> list of mongodb dataframes
:return: -> merged mongodb metrics
'''
# Read files
# Get column headers and gen dict with new col headers
colNamesMD = csvheaders2colNames(lmongo[0], 'node1')
df_MD = self.chainMerge(lmongo, colNamesMD, iterStart=2)
return df_MD
def chainMergeCassandra(self, lcassandra):
'''
:param lcassandra: -> list of cassandra dataframes
:return: -> merged Cassandra metrics
'''
# Read files
# Get column headers and gen dict with new col headers
colNamesCa = csvheaders2colNames(lcassandra[0], 'node1')
df_CA = self.chainMerge(lcassandra, colNamesCa, iterStart=2)
return df_CA
def chainMergeMongoDB(self, lmongo):
'''
:param lmongo: -> list of mongodb dataframes
:return: -> merged mongodb metrics
'''
# Read files
# Get column headers and gen dict with new col headers
colNamesMD = csvheaders2colNames(lmongo[0], 'node1')
df_MD = self.chainMerge(lmongo, colNamesMD, iterStart=2)
return df_MD
def chainMergeCassandra(self, lcassandra):
'''
:param lcassandra: -> list of cassandra dataframes
:return: -> merged Cassandra metrics
'''
# Read files
# Get column headers and gen dict with new col headers
colNamesCa = csvheaders2colNames(lcassandra[0], 'node1')
df_CA = self.chainMerge(lcassandra, colNamesCa, iterStart=2)
return df_CA
def chainMergeDN(self, lDN=None):
'''
:return: -> merged datanode metrics
'''
# Read files
if lDN is None:
allDN = glob.glob(os.path.join(self.dataDir, "DN_*.csv"))
else:
allDN = lDN
# Get column headers and gen dict with new col headers
colNamesDN = csvheaders2colNames(allDN[0], 'slave1')
df_DN = self.chainMerge(allDN, colNamesDN, iterStart=2)
return df_DN
def chainMergeDN(self, lDN=None):
'''
:return: -> merged datanode metrics
'''
# Read files
if lDN is None:
allDN = glob.glob(os.path.join(self.dataDir, "DN_*.csv"))
else:
allDN = lDN
# Get column headers and gen dict with new col headers
colNamesDN = csvheaders2colNames(allDN[0], 'slave1')
df_DN = self.chainMerge(allDN, colNamesDN, iterStart=2)
return df_DN