def testBinPacking(self):
"""
Tests the bin-packing method used by the cluster scaler.
"""
for test in range(50):
nodeShapes = [
Shape(wallTime=random.choice(list(range(1, 100))),
memory=random.choice(list(range(1, 10))),
cores=random.choice(list(range(1, 10))),
disk=random.choice(list(range(1, 10))),
preemptable=False) for i in range(5)
]
randomJobShape = lambda x: Shape(
wallTime=random.choice(list(range(1, (3 * x.wallTime) + 1))),
memory=random.choice(list(range(1, x.memory + 1))),
cores=random.choice(list(range(1, x.cores + 1))),
disk=random.choice(list(range(1, x.disk + 1))),
preemptable=False)
randomJobShapes = []
for nodeShape in nodeShapes:
numberOfJobs = random.choice(list(range(1, 1000)))
randomJobShapes.extend(
[randomJobShape(nodeShape) for i in range(numberOfJobs)])
startTime = time.time()
numberOfBins = binPacking(jobShapes=randomJobShapes,
nodeShapes=nodeShapes)
logger.info("Made the following node reservations: %s" %
numberOfBins)
def testBinPacking(self):
"""
Tests the bin-packing method used by the cluster scaler.
"""
for test in xrange(50):
nodeShape = Shape(wallTime=random.choice(range(1, 100)),
memory=random.choice(range(1, 10)),
cores=random.choice(range(1, 10)),
disk=random.choice(range(1, 10)))
randomJobShape = lambda x: Shape(wallTime=random.choice(range(1, (3 * x.wallTime) + 1)),
memory=random.choice(range(1, x.memory + 1)),
cores=random.choice(range(1, x.cores + 1)),
disk=random.choice(range(1, x.disk + 1)))
numberOfJobs = random.choice(range(1, 1000))
randomJobShapes = map(lambda i: randomJobShape(nodeShape), xrange(numberOfJobs))
startTime = time.time()
numberOfBins = binPacking(randomJobShapes, nodeShape)
logger.info("For node shape %s and %s job-shapes got %s bins in %s seconds, %s jobs/bin" %
(nodeShape, numberOfJobs, numberOfBins, time.time() - startTime, float(numberOfJobs)/numberOfBins))
def testBinPacking(self):
"""
Tests the bin-packing method used by the cluster scaler.
"""
for test in xrange(50):
nodeShape = Shape(wallTime=random.choice(range(1, 100)),
memory=random.choice(range(1, 10)),
cores=random.choice(range(1, 10)),
disk=random.choice(range(1, 10)))
randomJobShape = lambda x: Shape(wallTime=random.choice(range(1, (3 * x.wallTime) + 1)),
memory=random.choice(range(1, x.memory + 1)),
cores=random.choice(range(1, x.cores + 1)),
disk=random.choice(range(1, x.disk + 1)))
numberOfJobs = random.choice(range(1, 1000))
randomJobShapes = map(lambda i: randomJobShape(nodeShape), xrange(numberOfJobs))
startTime = time.time()
numberOfBins = binPacking(randomJobShapes, nodeShape)
logger.info("For node shape %s and %s job-shapes got %s bins in %s seconds, %s jobs/bin" %
(nodeShape, numberOfJobs, numberOfBins, time.time() - startTime, float(numberOfJobs)/numberOfBins))
