def test_compact(conn):
"""Test compacting of redundant data."""
def make_rows(timestamp):
return [
(10023 + i, timestamp, ('0.9919', '17'))
for i in range(100)
]
with closing(conn.cursor()) as cursor:
attribute_names = ['CCR', 'Drops']
datasource = DataSource.from_name(cursor, "integration-test")
entitytype = EntityType.from_name(cursor, "UtranCell")
timestamp = pytz.utc.localize(datetime.utcnow())
datapackage_a = DataPackage(
attribute_names=attribute_names,
rows=make_rows(timestamp)
)
datapackage_b = DataPackage(
attribute_names=attribute_names,
rows=make_rows(timestamp + timedelta(10))
)
attributes = datapackage_a.deduce_attributes()
attributestore = AttributeStore(datasource, entitytype, attributes)
attributestore.create(cursor)
attributestore.store_batch(cursor, datapackage_a)
conn.commit()
attributestore.store_batch(cursor, datapackage_b)
conn.commit()
count_query = (
"SELECT count(*) "
"FROM {0}").format(attributestore.history_table.render())
cursor.execute(count_query)
count, = cursor.fetchone()
# Row count should be the same as the stored batch sizes summed
eq_(count, len(datapackage_b.rows) + len(datapackage_a.rows))
attributestore.compact(cursor)
conn.commit()
cursor.execute(count_query)
count, = cursor.fetchone()
# Row count should be the same as the first stored batch size
eq_(count, len(datapackage_a.rows))
