def transfer_monitor():
for connection in all_connections:
connection.run('rm monitor.py')
connection.run('rm -rf logs')
transfer = Transfer(connection)
transfer.put('monitor.py')
connection.run('mkdir logs')
def example_streaming_kmeans():
transfer = Transfer(c2)
transfer.put(
'/Users/ronnie/Documents/spark_example/target/scala-2.12/spark_example_2.12-0.1.jar'
)
c2.run('source /etc/profile && cd $SPARK_HOME && bin/spark-submit '
'--class com.example.kmeans.KMeansExample '
'--master spark://' + str(remote_host) + ':7077 '
'--executor-memory 2g ~/spark_example_2.12-0.1.jar')
def example_uber():
# temporary
transfer = Transfer(c2)
transfer.put(
'/Users/ronnie/Documents/spark_example/target/scala-2.12/spark_example_2.12-0.1.jar'
)
c2.run('source /etc/profile && cd $SPARK_HOME && bin/spark-submit '
'--class uber.KMeansUber '
'--master spark://' + str(remote_host) + ':7077 '
'--executor-memory 2g ~/spark_example_2.12-0.1.jar')
def pgdump(c):
cid = host.run(
'docker container ls | grep awsdemo_db | head -c 12').stdout.strip()
host.run(
'''docker container exec %s sh -c "pg_dump -U awsdemo awsdemo | gzip > '/var/lib/postgresql/backups/awsdemo.gz'"'''
% cid)
host.run(
'docker cp %s:/var/lib/postgresql/backups/awsdemo.gz /tmp/awsdemo.gz' %
cid)
t = Transfer(host)
t.get('/tmp/awsdemo.gz')
def example_streaming():
# temporary
transfer = Transfer(c2)
transfer.put(
'/Users/ronnie/Documents/StreamingModeSpark/target/scala-2.12/streamingmodespark_2.12-0.1.jar'
)
c2.run('source /etc/profile && cd $SPARK_HOME && bin/spark-submit '
'--class example.stream.StructureStreaming '
'--master spark://' + str(remote_host) + ':7077 '
'--deploy-mode cluster '
'--executor-memory 100g '
'~/streamingmodespark_2.12-0.1.jar')
def example_datagenerator():
transfer = Transfer(c2)
transfer.put(
'/Users/ronnie/Documents/StreamingModeSpark/target/scala-2.12/streamingmodespark_2.12-0.1.jar'
)
c2.run('source /etc/profile && cd $SPARK_HOME && bin/spark-submit '
'--packages org.apache.spark:spark-sql-kafka-0-10_2.12:3.0.0 '
'--class example.stream.DataGenerator '
'~/streamingmodespark_2.12-0.1.jar '
'10000 '
'~/100-bytes-lines.txt '
'100')
def example_kafka_trial():
transfer = Transfer(c2)
transfer.put(
'/Users/ronnie/Documents/spark_example/target/scala-2.12/spark_example_2.12-0.1.jar'
)
# transfer.put('/Users/ronnie/Documents/datagenerator/kafka_producer_example.py')
c2.run('source /etc/profile && cd $SPARK_HOME && bin/spark-submit '
'--packages org.apache.spark:spark-streaming-kafka-0-10_2.12:3.0.0 '
'--class example.stream.DirectKafkaWordCount '
'~/spark_example_2.12-0.1.jar '
'localhost:9092 '
'consumer-group '
'test')
def example_streaming_kmeans():
# transfer package
transfer = Transfer(c2)
transfer.put(
'/Users/ronnie/Documents/spark_example/target/scala-2.12/spark_example_2.12-0.1.jar'
)
# transfer sample files
c2.run('source /etc/profile && cd $SPARK_HOME && bin/spark-submit '
'--packages org.apache.spark:spark-streaming-kafka-0-10_2.12:3.0.0 '
'--class example.stream.StreamingKMeansModelExample '
'~/spark_example_2.12-0.1.jar '
'localhost:9092 '
'consumer-group '
'test')
def test_networkwordcount():
# Transfer package
transfer = Transfer(master)
# transfer.put('/Users/ronnie/Documents/spark_example/target/scala-2.12/spark_example_2.12-0.1.jar')
# master.run('rm -rf kmeansModel')
transfer.put('./socketProducerExample.py')
start_datagenerator()
master.run(
'source /etc/profile && cd $SPARK_HOME && bin/run-example '
# '--packages org.apache.spark:spark-streaming-kafka-0-10_2.12:3.0.0 '
'org.apache.spark.examples.streaming.NetworkWordCount '
# '--master spark://' + str(master_host) + ':7077 --executor-memory 2g '
# '~/spark_example_2.12-0.1.jar '
'localhost '
'9999'
# 'test'
)
def transferFile(clusters='1'):
transfer = []
for i in range(int(clusters)):
transfer.append(Transfer(slaveConnections[i]))
for connection in transfer:
connection.put('./transferFile.py')
for i in range(int(clusters)):
slaveConnections[i].run('tmux new -d -s transferFile')
slaveConnections[i].run(
'tmux send -t transferFile python3\ ~/transferFile.py ENTER')
def testStructuredNetworkWordCount():
# Transfer package
transfer = Transfer(master)
# transfer.put('/Users/ronnie/Documents/spark_example/target/scala-2.12/spark_example_2.12-0.1.jar')
# master.run('rm -rf kmeansModel')
transfer.put('./socketProducerExample.py')
start_spark_cluster()
start_datagenerator()
master.run(
'source /etc/profile && cd $SPARK_HOME && bin/spark-submit '
'--class org.apache.spark.examples.sql.streaming.StructuredNetworkWordCount '
'--master spark://' + str(master_host) + ':7077 '
# '--deploy-mode cluster '
# '--supervise '
'--executor-memory 2g '
'examples/jars/spark-examples_2.12-3.0.0.jar '
'localhost '
'9999'
# 'test'
)
def stopProducer():
try:
producer.run('tmux kill-session -t socket')
transfer = Transfer(producer)
transfer.put('./retrieveProducerOutput.py')
producer.run('python3 ~/retrieveProducerOutput.py')
transfer.get('producerResult.txt')
producer.run('rm ~/data/_*')
except:
print('Socket already closed!')
def runExperiment(clusters='3',
numPorts='2',
time='60000',
executorMem='2g',
batchDuration='1'):
# transfer file
transfer = Transfer(master)
producerTransfer = Transfer(producer)
# Start Monitors
transferMonitor()
startMonitor()
# Transfer Producer
producerTransfer.put('./producer.py')
startProducer(numPorts)
# SBT packaging
os.system('sbt package')
# start start cluster
startSparkCluster(clusters)
# transfer jar
transfer.put(
'./target/scala-2.12/socketstreamingkmeansexperiment_2.12-0.1.jar')
try:
master.run('source /etc/profile && cd $SPARK_HOME && bin/spark-submit '
'--class Experiment '
'--master spark://' + str(masterHost) +
':7077 --executor-memory ' + executorMem + ' '
'~/socketstreamingkmeansexperiment_2.12-0.1.jar '
'192.168.122.153 '
'10000 ' + numPorts + ' ' + time + ' ' + batchDuration)
except:
print('Spark Crashed while running')
print('Application stopped at: {}'.format(
datetime.now().strftime("%H:%M:%S.%f")))
finally:
# transfer logs
stopMonitor()
transferLogs()
# Restart all VMs
stop()
def streaming_kmeans():
# Create Package
os.system('sbt package')
# Transfer package
transfer = Transfer(master)
transfer.put('./target/scala-2.12/spark_example_2.12-0.1.jar')
# Transfer datagenerator
transfer.put('./socketProducerExample.py')
# start spark cluster
start_spark_cluster()
start_datagenerator()
# start kafka
# start_kafka()
master.run('rm -rf kmeansModel')
master.run(
'source /etc/profile && cd $SPARK_HOME && bin/spark-submit '
# '--packages org.apache.spark:spark-streaming-kafka-0-10_2.12:3.0.0 '
'--class example.stream.StreamingKMeansModelExample '
# '--master spark://' + str(master_host) + ':7077 --executor-memory 2g '
'~/spark_example_2.12-0.1.jar '
'localhost '
'9999'
# 'test'
)
def createFiles():
transfer = Transfer(producer)
transfer.put('createFiles.py')
producer.run('python3 createFiles.py 2500 20000 6')
def createFilesWeibull():
transfer = Transfer(producer)
transfer.put('createFilesWeibull.py')
producer.run('python3 createFilesWeibull.py 10. 50000 6 300')
def closeMonitorPs():
for connection in slaveConnections + [master, producer]:
transfer = Transfer(connection)
transfer.put('closeMonitorPs.sh')
connection.run('chmod u+x closeMonitorPs.sh')
connection.run('./closeMonitorPs.sh')
def retreiveProducerOutput():
transfer = Transfer(master)
transfer.get('/home/ronald/tmp/spark-events/app-20201105205551-0000')
def transferToKafka(filename):
transfer = Transfer(kafka)
transfer.put(filename)
def transferFromServer(filename):
transfer = Transfer(conn)
transfer.get(filename)
def transferFromSlave(filename):
transfer = Transfer(slaveConnections[0])
transfer.get(filename)
def transfer_file_to(filename):
transfer = Transfer(c2)
transfer.put(filename)
def transferFromMaster(filename):
transfer = Transfer(master)
transfer.get(filename)
def runChecker():
# transfer checker
transfer = Transfer(master)
transfer.put('./checker.py')
master.run('source /etc/profile && cd $SPARK_HOME && bin/spark-submit '
'~/checker.py')
def testKafka(n='100'):
transfer = Transfer(kafka)
transfer.put('./kafkaProducer.py')
transfer.put('./kafkaConsumer.py')
startKafka(n)
def transferToProducer(filename):
transfer = Transfer(producer)
transfer.put(filename)
def pgdump(c):
cid = host.run('docker container ls | grep ' + APP_NAME.lower() +'_postgres | head -c 12').stdout.strip()
host.run('''docker container exec %s sh -c "pg_dump -U %s %s | gzip > '/var/lib/postgresql/backups/%s.gz'"''' % (cid, DB_USER, DB_DB, DB_DB))
host.run('docker cp %s:/var/lib/postgresql/backups/%s.gz /tmp/%s.gz' % (cid, DB_DB, DB_DB))
t = Transfer(host)
t.get('/tmp/%s.gz' % DB_NAME)
def transfer_to_all(filename):
for connection in all_connections:
transfer = Transfer(connection)
transfer.put(filename)
def trainModel():
# Transfer package
transfer = Transfer(master)
transferKafka = Transfer(kafka)
# Transfer datagenerator
transferKafka.put('./kafkaProducer.py')
# start kafka
startKafka()
# start spark cluster
startSparkCluster()
# Create Package
os.system('sbt package')
# Transfer files to master
transferKafka.get('/home/ronald/random_centers.csv')
transfer.put('./random_centers.csv')
transferKafka.get('/home/ronald/centers.csv')
transfer.put('./centers.csv')
transferKafka.get('/home/ronald/data.csv')
transfer.put('./data.csv')
# Transfer spark application
transfer.put(
'./target/scala-2.12/streamingkmeansmodeltrained_2.12-0.1.jar')
master.run(
'source /etc/profile && cd $SPARK_HOME && bin/spark-submit '
'--packages org.apache.spark:spark-streaming-kafka-0-10_2.12:3.0.0 '
'--class example.stream.StreamingKMeansModelTraining '
'--master spark://' + str(masterHost) + ':7077 --executor-memory 2g '
'~/streamingkmeansmodeltrained_2.12-0.1.jar '
'192.168.122.121:9092 '
'consumer-group '
'test')
runChecker()
stop()
def transfer_logs_out():
counter = 1
for connection in all_connections:
transfer = Transfer(connection)
transfer.get('logs/log.csv', 'log' + str(counter) + '.csv')
counter += 1
