def setUp(self):
MongoDBTestCase.setUp(self)
# Generate some fake workload sessions
for i in xrange(0, NUM_SESSIONS):
sess = self.metadata_db.Session()
sess['session_id'] = i
sess['ip_client'] = "client:%d" % (1234+i)
sess['ip_server'] = "server:5678"
sess['start_time'] = time.time()
sess['end_time'] = time.time() + 5
for j in xrange(0, NUM_OPS_PER_SESSION):
_id = str(random.random())
queryId = long((i<<16) + j)
responseContent = {"_id": _id}
responseId = (queryId<<8)
for f in xrange(0, NUM_FIELDS):
f_name = "field%02d" % f
if f % 2 == 0:
responseContent[f_name] = random.randint(0, 100)
else:
responseContent[f_name] = str(random.randint(1000, 100000))
## FOR
queryContent = { constants.REPLACE_KEY_DOLLAR_PREFIX + "query": responseContent }
op = workload.Session.operationFactory()
op['collection'] = COLLECTION_NAME
op['type'] = constants.OP_TYPE_QUERY
op['query_id'] = queryId
op['query_content'] = [ queryContent ]
op['resp_content'] = [ responseContent ]
op['resp_id'] = responseId
sess['operations'].append(op)
## FOR (ops)
sess.save()
## FOR (sess)
self.assertEqual(NUM_SESSIONS, self.metadata_db.Session.find().count())
self.converter = AbstractConverter(self.metadata_db, self.dataset_db)
def setUp(self):
MongoDBTestCase.setUp(self)
# Generate some fake workload sessions
for i in xrange(0, NUM_SESSIONS):
sess = self.metadata_db.Session()
sess["session_id"] = i
sess["ip_client"] = "client:%d" % (1234 + i)
sess["ip_server"] = "server:5678"
sess["start_time"] = time.time()
sess["end_time"] = time.time() + 5
for j in xrange(0, NUM_OPS_PER_SESSION):
_id = str(random.random())
queryId = long((i << 16) + j)
responseContent = {"_id": _id}
responseId = queryId << 8
for f in xrange(0, NUM_FIELDS):
f_name = "field%02d" % f
if f % 2 == 0:
responseContent[f_name] = random.randint(0, 100)
else:
responseContent[f_name] = str(random.randint(1000, 100000))
## FOR
queryContent = {constants.REPLACE_KEY_DOLLAR_PREFIX + "query": responseContent}
op = workload.Session.operationFactory()
op["collection"] = COLLECTION_NAME
op["type"] = constants.OP_TYPE_QUERY
op["query_id"] = queryId
op["query_content"] = [queryContent]
op["resp_content"] = [responseContent]
op["resp_id"] = responseId
sess["operations"].append(op)
## FOR (ops)
sess.save()
## FOR (sess)
self.assertEqual(NUM_SESSIONS, self.metadata_db.Session.find().count())
self.converter = AbstractConverter(self.metadata_db, self.dataset_db)
class TestAbstractConverter(MongoDBTestCase):
def setUp(self):
MongoDBTestCase.setUp(self)
# Generate some fake workload sessions
for i in xrange(0, NUM_SESSIONS):
sess = self.metadata_db.Session()
sess["session_id"] = i
sess["ip_client"] = "client:%d" % (1234 + i)
sess["ip_server"] = "server:5678"
sess["start_time"] = time.time()
sess["end_time"] = time.time() + 5
for j in xrange(0, NUM_OPS_PER_SESSION):
_id = str(random.random())
queryId = long((i << 16) + j)
responseContent = {"_id": _id}
responseId = queryId << 8
for f in xrange(0, NUM_FIELDS):
f_name = "field%02d" % f
if f % 2 == 0:
responseContent[f_name] = random.randint(0, 100)
else:
responseContent[f_name] = str(random.randint(1000, 100000))
## FOR
queryContent = {constants.REPLACE_KEY_DOLLAR_PREFIX + "query": responseContent}
op = workload.Session.operationFactory()
op["collection"] = COLLECTION_NAME
op["type"] = constants.OP_TYPE_QUERY
op["query_id"] = queryId
op["query_content"] = [queryContent]
op["resp_content"] = [responseContent]
op["resp_id"] = responseId
sess["operations"].append(op)
## FOR (ops)
sess.save()
## FOR (sess)
self.assertEqual(NUM_SESSIONS, self.metadata_db.Session.find().count())
self.converter = AbstractConverter(self.metadata_db, self.dataset_db)
## DEF
def testAddQueryHashes(self):
# First make sure that all of the operations' query hashes are null
for sess in self.metadata_db.Session.find():
self.assertNotEqual(0, len(sess["operations"]))
for op in sess["operations"]:
self.assertIsNone(op["query_hash"])
## FOR
# Now add the hashes. They should all be the same
self.converter.addQueryHashes()
firstHash = None
for sess in self.metadata_db.Session.find():
self.assertNotEqual(0, len(sess["operations"]))
for op in sess["operations"]:
if not firstHash:
firstHash = op["query_hash"]
self.assertIsNotNone(firstHash)
self.assertEqual(firstHash, op["query_hash"])
## FOR
## DEF
def testPostProcess(self):
"""
Check whether we can successfully extract the database schema
into our internal catalog
"""
Reconstructor(self.metadata_db, self.dataset_db).process()
self.converter.postProcess()
col_info = self.metadata_db.Collection.one({"name": COLLECTION_NAME})
# pprint(col_info)
# Workload-derived Attributes
self.assertEqual(NUM_SESSIONS * NUM_OPS_PER_SESSION, col_info["workload_queries"])
self.assertAlmostEqual(1.0, col_info["workload_percent"])
# Fields
# Add one for the '_id' field count
self.assertEqual(NUM_FIELDS + 1, len(col_info["fields"]))
for k, field in col_info["fields"].iteritems():
self.assertEqual(NUM_SESSIONS * NUM_OPS_PER_SESSION, field["query_use_count"])
## DEF
def testProcessDataFieldsSimple(self):
doc = {
"int": 123,
"str": "abc",
"float": 123.4,
# TODO
#'list': range(10),
#'dict': ....
}
col_info = catalog.Collection()
col_info["data_size"] = 0
fields = {}
self.converter.processDataFields(col_info, fields, doc)
self.assertIsNotNone(fields)
self.assertEquals(dict, type(fields))
for key, val in doc.iteritems():
self.assertIn(key, fields)
f = fields[key]
self.assertIsNotNone(f)
self.assertEquals(key, f["type"])
## FOR
## DEF
def testProcessDataFields(self):
doc = {
"similar_artists": ["50e130f676d6081483d7aeaf90702caa/7", "3b6fac3e5e112ae35414480ccc5eb154/23"],
"name": "596ea227ea0ce4dadbca2f06bddd30c9/15",
"created": {"\$date": 1335871184519L},
"image": {
"large": "1b942d952ccd004325c997c012d49354/49",
"extralarge": "bd11cf67bd8ee7653a1cfdf782c4ffaa/49",
"small": "f5728a43a9e3efac9a0670cc66c2229f/48",
"medium": "00b6d53c70a4fe656a4fc867ed9aceed/48",
"mega": "6998e2abb589312f0fd358943865bf3c/61",
},
"last_modified": {"\$date": datetime.now()},
"alias_md5s": ["2b763d64b83180c5512a962d5c4d5115/34"],
"aliases": ["3019b6686229c4cf5089431332dee196/15"],
}
col_info = catalog.Collection()
col_info["data_size"] = 0
fields = {}
self.converter.processDataFields(col_info, fields, doc)
self.assertIsNotNone(fields)
self.assertNotEqual(len(fields), 0)
# pprint(fields)
# Check to make sure that we have a field entry for each
# key in our original document. We will need to check recursively
# to make sure that our nested keys get picked up
for key, val in doc.iteritems():
self.assertIn(key, fields)
f = fields[key]
self.assertNotEqual(f, None)
class TestAbstractConverter(MongoDBTestCase):
def setUp(self):
MongoDBTestCase.setUp(self)
# Generate some fake workload sessions
for i in xrange(0, NUM_SESSIONS):
sess = self.metadata_db.Session()
sess['session_id'] = i
sess['ip_client'] = "client:%d" % (1234+i)
sess['ip_server'] = "server:5678"
sess['start_time'] = time.time()
sess['end_time'] = time.time() + 5
for j in xrange(0, NUM_OPS_PER_SESSION):
_id = str(random.random())
queryId = long((i<<16) + j)
responseContent = {"_id": _id}
responseId = (queryId<<8)
for f in xrange(0, NUM_FIELDS):
f_name = "field%02d" % f
if f % 2 == 0:
responseContent[f_name] = random.randint(0, 100)
else:
responseContent[f_name] = str(random.randint(1000, 100000))
## FOR
queryContent = { constants.REPLACE_KEY_DOLLAR_PREFIX + "query": responseContent }
op = workload.Session.operationFactory()
op['collection'] = COLLECTION_NAME
op['type'] = constants.OP_TYPE_QUERY
op['query_id'] = queryId
op['query_content'] = [ queryContent ]
op['resp_content'] = [ responseContent ]
op['resp_id'] = responseId
sess['operations'].append(op)
## FOR (ops)
sess.save()
## FOR (sess)
self.assertEqual(NUM_SESSIONS, self.metadata_db.Session.find().count())
self.converter = AbstractConverter(self.metadata_db, self.dataset_db)
## DEF
def testAddQueryHashes(self):
# First make sure that all of the operations' query hashes are null
for sess in self.metadata_db.Session.find():
self.assertNotEqual(0, len(sess['operations']))
for op in sess['operations']:
self.assertIsNone(op['query_hash'])
## FOR
# Now add the hashes. They should all be the same
self.converter.addQueryHashes()
firstHash = None
for sess in self.metadata_db.Session.find():
self.assertNotEqual(0, len(sess['operations']))
for op in sess['operations']:
if not firstHash:
firstHash = op['query_hash']
self.assertIsNotNone(firstHash)
self.assertEqual(firstHash, op['query_hash'])
## FOR
## DEF
def testPostProcess(self):
"""
Check whether we can successfully extract the database schema
into our internal catalog
"""
Reconstructor(self.metadata_db, self.dataset_db).process()
self.converter.postProcess()
col_info = self.metadata_db.Collection.one({"name": COLLECTION_NAME})
# pprint(col_info)
# Workload-derived Attributes
self.assertEqual(NUM_SESSIONS*NUM_OPS_PER_SESSION, col_info['workload_queries'])
self.assertAlmostEqual(1.0, col_info['workload_percent'])
# Fields
# Add one for the '_id' field count
self.assertEqual(NUM_FIELDS + 1, len(col_info['fields']))
for k,field in col_info['fields'].iteritems():
self.assertEqual(NUM_SESSIONS*NUM_OPS_PER_SESSION, field['query_use_count'])
## DEF
def testProcessDataFieldsSimple(self):
doc = {
'int': 123,
'str': 'abc',
'float': 123.4,
# TODO
#'list': range(10),
#'dict': ....
}
col_info = catalog.Collection()
col_info['data_size'] = 0
fields = { }
self.converter.processDataFields(col_info, fields, doc)
self.assertIsNotNone(fields)
self.assertEquals(dict, type(fields))
for key, val in doc.iteritems():
self.assertIn(key, fields)
f = fields[key]
self.assertIsNotNone(f)
self.assertEquals(key, f['type'])
## FOR
## DEF
def testProcessDataFields(self):
doc = {
"similar_artists" : [
"50e130f676d6081483d7aeaf90702caa/7",
"3b6fac3e5e112ae35414480ccc5eb154/23",
],
"name" : "596ea227ea0ce4dadbca2f06bddd30c9/15",
"created" : {
"\$date" : 1335871184519l,
},
"image" : {
"large" : "1b942d952ccd004325c997c012d49354/49",
"extralarge" : "bd11cf67bd8ee7653a1cfdf782c4ffaa/49",
"small" : "f5728a43a9e3efac9a0670cc66c2229f/48",
"medium" : "00b6d53c70a4fe656a4fc867ed9aceed/48",
"mega" : "6998e2abb589312f0fd358943865bf3c/61"
},
"last_modified" : {
"\$date" : datetime.now(),
},
"alias_md5s" : [
"2b763d64b83180c5512a962d5c4d5115/34"
],
"aliases" : [
"3019b6686229c4cf5089431332dee196/15"
]
}
col_info = catalog.Collection()
col_info['data_size'] = 0
fields = { }
self.converter.processDataFields(col_info, fields, doc)
self.assertIsNotNone(fields)
self.assertNotEqual(len(fields), 0)
# pprint(fields)
# Check to make sure that we have a field entry for each
# key in our original document. We will need to check recursively
# to make sure that our nested keys get picked up
for key, val in doc.iteritems():
self.assertIn(key, fields)
f = fields[key]
self.assertNotEqual(f, None)
