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