def test_bloom_intersection(octopus, clean_db):
"""
Verify that bloom_intersection works
"""
octopus.create_stream('test_bloom_stream', x='int', k='int')
q = """
SELECT k::int, bloom_agg(x::integer) FROM test_bloom_stream GROUP BY k
"""
desc = ('k', 'x')
octopus.create_cv('test_bloom_intersection', q)
rows = []
for i in range(10000):
rows.append((0, 2 * i))
rows.append((1, i))
octopus.insert('test_bloom_stream', desc, rows)
cvq = """
SELECT bloom_cardinality(bloom_intersection_agg(bloom_agg))
FROM test_bloom_intersection
"""
result = list(octopus.execute(cvq))
assert len(result) == 1
result = result[0]
assert result[0] == 5530
def test_combine_in_view(octopus, clean_db):
"""
Verify that combines in views on top of continuous views work
"""
q = """
SELECT x::integer, avg(y::integer) FROM stream0 GROUP BY x
"""
desc = ('x', 'y')
octopus.create_stream('stream0', x='int', y='float8')
octopus.create_cv('test_combine_view', q)
octopus.execute(
'CREATE VIEW v AS SELECT combine(avg) FROM test_combine_view')
rows = []
for n in range(10000):
rows.append((random.randint(1, 256), random.randint(1, 1024)))
octopus.insert('stream0', desc, rows)
view = list(octopus.execute('SELECT * FROM v'))
assert len(view) == 1
expected = sum(r[1] for r in rows) / float(len(rows))
assert abs(float(view[0][0]) - expected) < 0.00001
octopus.execute('DROP VIEW v')
def test_bloom_agg_hashing(octopus, clean_db):
"""
Verify that bloom_agg correctly hashes different input types
"""
octopus.create_stream('test_bloom_stream', x='int', y='text', z='float8')
q = """
SELECT bloom_agg(x::integer) AS i,
bloom_agg(y::text) AS t,
bloom_agg(z::float8) AS f FROM test_bloom_stream
"""
desc = ('x', 'y', 'z')
octopus.create_cv('test_bloom_hashing', q)
rows = []
for n in range(10000):
rows.append((n, '%d' % n, float(n)))
rows.append((n, '%05d' % n, float(n)))
octopus.insert('test_bloom_stream', desc, rows)
cvq = """
SELECT bloom_cardinality(i),
bloom_cardinality(t), bloom_cardinality(f) FROM test_bloom_hashing
"""
result = list(octopus.execute(cvq))
assert len(result) == 1
result = result[0]
assert result[0] == 8879
assert result[1] == 15614
assert result[2] == 8855
def test_join_multiple_tables(octopus, clean_db):
"""
Verify that stream-table joins involving multiple tables work
"""
num_cols = 8
join_cols = [0]
t0_cols = dict([('col%d' % n, 'integer') for n in range(num_cols)])
t1_cols = dict([('col%d' % n, 'integer') for n in range(num_cols)])
octopus.create_table('t0', **t0_cols)
octopus.create_table('t1', **t1_cols)
octopus.create_stream('stream0', **t0_cols)
q = """
SELECT s.col0::integer FROM t0 JOIN t1 ON t0.col0 = t1.col0
JOIN stream0 s ON t1.col0 = s.col0
"""
t0 = _generate_rows(num_cols, 64)
t1 = _generate_rows(num_cols, 64)
s = _generate_rows(num_cols, 64)
_insert(octopus, 't1', t1, 0.1)
_insert(octopus, 't0', t0, 0.1)
octopus.create_cv('test_join_multi', q)
_insert(octopus, 'stream0', s)
expected = _join(t0, _join(s, t1, join_cols), join_cols)
result = octopus.execute('SELECT COUNT(*) FROM test_join_multi').first()
assert result['count'] == len(expected)
def test_indexed(octopus, clean_db):
"""
Verify that stream-table joins involving indexed tables work
"""
octopus.create_stream('stream0', x='int', y='int')
q = """
SELECT stream0.x::integer, count(*) FROM stream0
JOIN test_indexed_t t ON stream0.x = t.x GROUP BY stream0.x
"""
octopus.create_table('test_indexed_t', x='integer', y='integer')
octopus.execute('CREATE INDEX idx ON test_indexed_t(x)')
t = _generate_rows(2, 1000)
s = _generate_rows(2, 1000)
octopus.insert('test_indexed_t', ('x', 'y'), t)
time.sleep(0.1)
octopus.create_cv('test_indexed', q)
octopus.insert('stream0', ('x', 'y'), s)
expected = _join(s, t, [0])
result = octopus.execute('SELECT sum(count) FROM test_indexed').first()
assert result['sum'] == len(expected)
def test_join_across_batches(octopus, clean_db):
"""
Verify that stream-table joins are properly built when they
span across multiple input batches
"""
num_cols = 4
join_cols = [0]
t_cols = dict([('col%d' % n, 'integer') for n in range(num_cols)])
octopus.create_table('batch', **t_cols)
octopus.create_stream('stream0', **t_cols)
q = """
SELECT s.col0::integer FROM batch JOIN stream0 s ON batch.col0 = s.col0
"""
t = _generate_rows(num_cols, 64)
_insert(octopus, 'batch', t, 0.1)
s = _generate_rows(num_cols, 64)
octopus.create_cv('test_batched_join', q)
_insert(octopus, 'stream0', s)
expected = _join(t, s, join_cols)
result = octopus.execute('SELECT COUNT(*) FROM test_batched_join').first()
assert result['count'] == len(expected)
def test_incremental_join(octopus, clean_db):
"""
Verify that join results increase appropriately as we incrementally
add stream events to the input
"""
num_cols = 4
join_cols = [0, 1]
t_cols = dict([('col%d' % n, 'integer') for n in range(num_cols)])
octopus.create_table('inc', **t_cols)
octopus.create_stream('stream0', **t_cols)
q = """
SELECT s.col0::integer FROM inc JOIN stream0 s ON inc.col0 = s.col0
AND inc.col1 = s.col1::integer
"""
t = _generate_rows(num_cols, 64)
_insert(octopus, 'inc', t, 0.1)
octopus.create_cv('test_join', q)
s = []
for n in range(2):
row = _generate_row(num_cols)
_insert(octopus, 'stream0', [row])
s.append(row)
expected = _join(t, s, join_cols)
result = octopus.execute('SELECT COUNT(*) FROM test_join').first()
assert result['count'] == len(expected)
def test_user_low_and_high_card(octopus, clean_db):
"""
Verify that HLL's with low and high cardinalities are correcly combined
"""
octopus.create_stream('test_hll_stream', x='int', k='integer')
q = """
SELECT k::integer, hll_agg(x::integer) FROM test_hll_stream GROUP BY k
"""
desc = ('k', 'x')
octopus.create_cv('test_hll_agg', q)
# Low cardinalities
rows = []
for n in range(1000):
rows.append((0, random.choice((-1, -2))))
rows.append((1, random.choice((-3, -4))))
# High cardinalities
for n in range(10000):
rows.append((2, n))
rows.append((3, n))
octopus.insert('test_hll_stream', desc, rows)
result = octopus.execute('SELECT hll_cardinality(combine(hll_agg)) '
'FROM test_hll_agg WHERE k in (0, 1)').first()
assert result[0] == 4
result = octopus.execute('SELECT hll_cardinality(combine(hll_agg)) '
'FROM test_hll_agg WHERE k in (2, 3)').first()
assert result[0] == 9976
result = octopus.execute('SELECT hll_cardinality(combine(hll_agg)) '
'FROM test_hll_agg').first()
assert result[0] == 9983
def test_cmsketch_agg(octopus, clean_db):
"""
Test cmsketch_agg, cmsketch_merge_agg, cmsketch_cdf, cmsketch_quantile
"""
octopus.create_stream('test_cmsketch_stream', k='int', x='int')
q = """
SELECT k::integer, cmsketch_agg(x::int) AS c FROM test_cmsketch_stream
GROUP BY k
"""
desc = ('k', 'x')
octopus.create_cv('test_cmsketch_agg', q)
rows = []
for n in range(1000):
rows.append((0, n % 20))
rows.append((1, n % 50))
octopus.insert('test_cmsketch_stream', desc, rows)
result = list(octopus.execute(
'SELECT cmsketch_frequency(c, 10) AS x, cmsketch_frequency(c, 40) AS y, '
'cmsketch_frequency(c, 60) FROM test_cmsketch_agg ORDER BY k').fetchall())
assert len(result) == 2
assert tuple(result[0]) == (50, 0, 0)
assert tuple(result[1]) == (20, 20, 0)
result = list(octopus.execute(
'SELECT cmsketch_frequency(combine(c), 10) AS x, '
'cmsketch_frequency(combine(c), 40) AS y, cmsketch_frequency(combine(c), 60) '
'FROM test_cmsketch_agg').fetchall())
assert len(result) == 1
assert tuple(result[0]) == (70, 20, 0)
def test_single_continuous_view(octopus, clean_db):
"""
Verify that specific continuous views can be dropped and restored
"""
octopus.create_stream('stream0', x='int')
octopus.create_cv('test_single0', 'SELECT COUNT(*) FROM stream0')
octopus.create_cv('test_single1', 'SELECT COUNT(*) FROM stream0')
octopus.insert('stream0', ('x',), [(x,) for x in range(10)])
result = octopus.execute('SELECT count FROM test_single0').first()
assert result['count'] == 10
result = octopus.execute('SELECT count FROM test_single1').first()
assert result['count'] == 10
_dump(octopus, 'test_single.sql', tables=['test_single0', 'stream0', 'test_single0_mrel'])
octopus.drop_all()
_restore(octopus, 'test_single.sql')
result = octopus.execute('SELECT count FROM test_single0').first()
assert result['count'] == 10
# We didn't dump this one
result = list(octopus.execute('SELECT * FROM pg_class WHERE relname LIKE \'%%test_single1%%\''))
assert not result
def test_join_with_where(octopus, clean_db):
"""
Verify that stream-table joins using a WHERE clause work properly
"""
num_cols = 4
q = """
SELECT s.col0::integer FROM stream0 s, wt WHERE s.col0 = 1 AND wt.col0 = 1
"""
wt_cols = dict([('col%d' % n, 'integer') for n in range(num_cols)])
octopus.create_table('wt', **wt_cols)
octopus.create_table('wt_s', **wt_cols)
wt = _generate_rows(num_cols, 64)
s = _generate_rows(num_cols, 64)
_insert(octopus, 'wt', wt, 0.1)
_insert(octopus, 'wt_s', s, 0.1)
octopus.create_stream('stream0', **wt_cols)
octopus.create_cv('test_join_where', q)
_insert(octopus, 'stream0', s)
expected = octopus.execute('SELECT COUNT(*) FROM wt_s s, wt WHERE s.col0 = 1 AND wt.col0 = 1').first()
result = octopus.execute('SELECT COUNT(*) FROM test_join_where').first()
assert result['count'] == expected['count']
def test_prepared_extended(octopus, clean_db):
"""
Verify that we can write to streams using the extended protocol. This test
shells out to a binary because psycopg2 doesn't use the extended protocol.
"""
octopus.create_stream('extended_stream', x='int', y='int', z='int')
q = """
SELECT COUNT(x::integer) AS x, COUNT(y::integer) AS y, COUNT(z::integer) AS z FROM extended_stream
"""
octopus.create_cv('test_prepared_extended', q)
# This will insert 1000 via a paramaterized insert, and 1000 via unparamaterized insert
cmd = ['./extended', 'octopus', str(octopus.port), 'extended_stream', '1000']
stdout, stderr = subprocess.Popen(cmd).communicate()
assert stdout is None
assert stderr is None
rows = list(octopus.execute('SELECT x, y, z FROM test_prepared_extended'))
assert len(rows) == 1
result = rows[0]
assert result['x'] == 2000
assert result['y'] == 2000
assert result['z'] == 2000
def test_filter_clause(octopus, clean_db):
"""
Verify that FILTER clauses work on aggregates and sliding window aggregates
"""
octopus.create_stream('test_filter_stream', x='int')
q = """
SELECT SUM(x::int) FILTER (WHERE mod(x, 2) = 0) AS sum2, SUM(x::int) FILTER (WHERE mod(x, 3) = 0) AS sum3 FROM test_filter_stream
"""
sw = """
WHERE arrival_timestamp > clock_timestamp() - interval '30 second'
"""
octopus.create_cv('test_filter', q)
octopus.create_cv('test_filter_sw', '%s %s' % (q, sw))
desc = ('x', )
rows = []
for n in range(1000):
rows.append((n, ))
octopus.insert('test_filter_stream', desc, rows)
sum2 = sum(filter(lambda x: x % 2 == 0, map(lambda x: x[0], rows)))
sum3 = sum(filter(lambda x: x % 3 == 0, map(lambda x: x[0], rows)))
result1 = octopus.execute('SELECT * FROM test_filter').first()
result2 = octopus.execute('SELECT * FROM test_filter_sw').first()
assert result1['sum2'] == result2['sum2'] == sum2
assert result1['sum3'] == result2['sum3'] == sum3
def test_fss_agg(octopus, clean_db):
octopus.create_stream('test_fss_stream', x='int', k='text')
q = """
SELECT k::text, fss_agg(x::int, 5) FROM test_fss_stream
GROUP BY k
"""
desc = ('k', 'x')
octopus.create_cv('test_fss_agg', q)
items = range(14)
random.shuffle(items)
a_items = items
b_items = list(reversed(items))
values = map(lambda i: ('a', i), get_geometric_dist(a_items))
values.extend(map(lambda i: ('b', i), get_geometric_dist(b_items)))
random.shuffle(values)
octopus.insert('test_fss_stream', desc, values)
result = list(
octopus.execute(
'SELECT k, fss_topk_values(fss_agg) FROM test_fss_agg ORDER BY k'))
topk = map(int, result[0][1].rstrip('}').lstrip('{').split(','))
assert sorted(topk) == sorted(a_items[-5:])
topk = map(int, result[1][1].rstrip('}').lstrip('{').split(','))
assert sorted(topk) == sorted(b_items[-5:])
def test_restart_recovery(octopus, clean_db):
octopus.create_stream('stream0', x='int')
q = 'SELECT COUNT(*) FROM stream0'
octopus.create_cv('test_restart_recovery', q)
octopus.insert('stream0', ['x'], [(1, ), (1, )])
result = octopus.execute('SELECT * FROM test_restart_recovery').first()
assert result['count'] == 2
# Need to sleep here, otherwise on restart the materialization table is
# empty. Not sure why.
time.sleep(0.1)
# Restart.
octopus.stop()
octopus.run()
result = octopus.execute('SELECT * FROM test_restart_recovery').first()
assert result['count'] == 2
octopus.insert('stream0', ['x'], [(1, ), (1, )])
result = octopus.execute('SELECT * FROM test_restart_recovery').first()
assert result['count'] == 4
def test_simple_crash(octopus, clean_db):
"""
Test simple worker and combiner crashes.
"""
octopus.create_stream('stream0', x='int')
q = 'SELECT COUNT(*) FROM stream0'
octopus.create_cv('test_simple_crash', q)
octopus.insert('stream0', ['x'], [(1, ), (1, )])
result = octopus.execute('SELECT * FROM test_simple_crash').first()
assert result['count'] == 2
# This batch can potentially get lost.
octopus.insert('stream0', ['x'], [(1, ), (1, )])
assert kill_worker()
octopus.insert('stream0', ['x'], [(1, ), (1, )])
result = octopus.execute('SELECT * FROM test_simple_crash').first()
assert result['count'] in [4, 6]
# This batch can potentially get lost.
octopus.insert('stream0', ['x'], [(1, ), (1, )])
assert kill_combiner()
octopus.insert('stream0', ['x'], [(1, ), (1, )])
result = octopus.execute('SELECT * FROM test_simple_crash').first()
assert result['count'] in [6, 8, 10]
# To ensure that all remaining events in ZMQ queues have been consumed
time.sleep(2)
def test_bloom_contains(octopus, clean_db):
"""
Verify that bloom_contains works
"""
octopus.create_stream('test_bloom_stream', x='int')
q = """
SELECT bloom_agg(x::integer) FROM test_bloom_stream
"""
desc = ('x')
octopus.create_cv('test_bloom_contains', q)
rows = []
for i in range(10000):
rows.append((2 * i, ))
octopus.insert('test_bloom_stream', desc, rows)
cvq = """
SELECT bloom_contains(bloom_agg, 0), bloom_contains(bloom_agg, 5000),
bloom_contains(bloom_agg, 1), bloom_contains(bloom_agg, 5001)
FROM test_bloom_contains
"""
result = list(octopus.execute(cvq))
assert len(result) == 1
result = result[0]
assert result[0] == True
assert result[1] == True
assert result[2] == False
assert result[3] == False
def assert_result_changes(func, args):
"""
Verifies that the result of the given function changes with time
"""
octopus.create_stream('stream0', x='int', y='text', z='int')
name = 'assert_%s_decreases' % func
octopus.create_cv(
name,
"SELECT %s(%s) FROM stream0 WHERE arrival_timestamp > clock_timestamp() - interval '2 seconds'"
% (func, args))
rows = [(n, str(n), n + 1) for n in range(1000)]
octopus.insert('stream0', ('x', 'y', 'z'), rows)
current = 1
results = []
while current:
row = octopus.execute('SELECT * FROM %s' % name).first()
current = row[func]
if current is None:
break
results.append(current)
# Verify that we actually read something
assert results
octopus.drop_cv(name)
def test_concurrent_vacuum_full(octopus, clean_db):
octopus.create_stream('test_vacuum_stream', x='int')
octopus.create_cv(
'test_vacuum_full',
'SELECT x::int, COUNT(*) FROM test_vacuum_stream GROUP BY x')
stop = False
def insert():
while not stop:
values = [(random.randint(0, 1000000), ) for _ in xrange(1000)]
octopus.insert('test_vacuum_stream', ('x', ), values)
time.sleep(0.01)
threads = [threading.Thread(target=insert) for _ in range(4)]
map(lambda t: t.start(), threads)
# Insert data for a little bit so we have enough work to do while
# vacuuming.
time.sleep(20)
conn = psycopg2.connect('dbname=octopus user=%s host=localhost port=%s' %
(getpass.getuser(), octopus.port))
conn.set_isolation_level(psycopg2.extensions.ISOLATION_LEVEL_AUTOCOMMIT)
cur = conn.cursor()
cur.execute('VACUUM FULL test_vacuum_full')
conn.close()
# Now kill the insert threads.
stop = True
map(lambda t: t.join(), threads)
def test_simple_aggs(octopus, clean_db):
"""
Verify that combines work properly on simple aggs
"""
q = """
SELECT x::integer %% 10 AS k,
avg(x), sum(y::float8), count(*) FROM stream0 GROUP BY k;
"""
desc = ('x', 'y')
octopus.create_stream('stream0', x='int', y='float8')
octopus.create_cv('test_simple_aggs', q)
octopus.create_table('test_simple_aggs_t', x='integer', y='float8')
rows = []
for n in range(10000):
row = (random.randint(0, 1000), random.random())
rows.append(row)
octopus.insert('stream0', desc, rows)
octopus.insert('test_simple_aggs_t', desc, rows)
table_result = list(
octopus.execute(
'SELECT avg(x), sum(y::float8), count(*) FROM test_simple_aggs_t'))
cv_result = list(
octopus.execute(
'SELECT combine(avg), combine(sum), combine(count) FROM test_simple_aggs'
))
assert len(table_result) == len(cv_result)
for tr, cr in zip(table_result, cv_result):
assert abs(tr[0] - cr[0]) < 0.00001
assert abs(tr[1] - cr[1]) < 0.00001
assert abs(tr[2] - cr[2]) < 0.00001
def test_multiple_databases(octopus, clean_db):
conn = psycopg2.connect('dbname=octopus user=%s host=localhost port=%s' %
(getpass.getuser(), octopus.port))
conn.set_isolation_level(ISOLATION_LEVEL_AUTOCOMMIT)
cur = conn.cursor()
cur.execute('CREATE DATABASE tmp_octopus')
cur.close()
q = 'SELECT x::int FROM dbstream'
octopus.create_stream('dbstream', x='int')
octopus.create_cv('test_multiple_databases', q)
# Insert data in first database.
octopus.insert('dbstream', ['x'], map(lambda x: (x, ), range(0, 10, 2)))
result = octopus.execute('SELECT * FROM test_multiple_databases')
assert sorted(row['x'] for row in result) == range(0, 10, 2)
# Create same CV in the other database, make sure its created and write different data to it.
tmp_conn = psycopg2.connect(
'dbname=tmp_octopus user=%s host=localhost port=%s' %
(getpass.getuser(), octopus.port))
cur = tmp_conn.cursor()
cur.execute('CREATE STREAM dbstream (x int)')
cur.execute('CREATE CONTINUOUS VIEW test_multiple_databases AS %s' % q)
tmp_conn.commit()
cur.execute('INSERT INTO dbstream (x) VALUES %s' %
', '.join(map(lambda x: '(%d)' % x, range(1, 11, 2))))
cur.execute('SELECT * FROM test_multiple_databases')
tmp_conn.commit()
assert sorted(row[0] for row in cur) == range(1, 11, 2)
# Ensure that the data written to the other database isn't seen by the first database.
result = octopus.execute('SELECT * FROM test_multiple_databases')
assert sorted(row['x'] for row in result) == range(0, 10, 2)
# Insert new data to both databases.
octopus.insert('dbstream', ['x'], map(lambda x: (x, ), range(10, 20, 2)))
cur.execute('INSERT INTO dbstream (x) VALUES %s' %
', '.join(map(lambda x: '(%d)' % x, range(11, 21, 2))))
# Ensure both databases still saw the data written out to them.
result = octopus.execute('SELECT * FROM test_multiple_databases')
assert sorted(row['x'] for row in result) == range(0, 20, 2)
cur.execute('SELECT * FROM test_multiple_databases')
tmp_conn.commit()
assert sorted(row[0] for row in cur) == range(1, 21, 2)
cur.close()
tmp_conn.close()
cur = conn.cursor()
cur.execute('DROP DATABASE tmp_octopus')
cur.close()
conn.close()
def test_create_views(octopus, clean_db):
cvs = []
octopus.create_stream('stream0', x='int')
q = 'SELECT count(*) FROM stream0'
for i in xrange(1, MAX_CQS):
cvs.append('cv_%d' % i)
octopus.create_cv(cvs[-1], q)
try:
octopus.create_cv('cv_fail', q)
assert False
except Exception, e:
assert 'maximum number of continuous queries exceeded' in e.message
def test_uniqueness(octopus, clean_db):
octopus.create_stream('stream0', x='int')
octopus.create_cv('uniqueness',
'SELECT x::int, count(*) FROM stream0 GROUP BY x')
for i in range(10):
rows = [((10000 * i) + j, ) for j in xrange(10000)]
octopus.insert('stream0', ('x', ), rows)
count = octopus.execute('SELECT count(*) FROM uniqueness').first()['count']
distinct_count = octopus.execute(
'SELECT count(DISTINCT x) FROM uniqueness').first()['count']
assert count == distinct_count
def test_tdigest_agg(octopus, clean_db):
"""
Test tdigest_agg, tdigest_merge_agg, tdigest_cdf, tdigest_quantile
"""
q = """
SELECT k::integer, tdigest_agg(x::int) AS t FROM test_tdigest_stream
GROUP BY k
"""
desc = ('k', 'x')
octopus.create_stream('test_tdigest_stream', k='int', x='int')
octopus.create_cv('test_tdigest_agg', q)
rows = []
for _ in range(10):
for n in range(1000):
rows.append((0, n))
rows.append((1, n + 500))
octopus.insert('test_tdigest_stream', desc, rows)
result = list(
octopus.execute(
'SELECT tdigest_quantile(t, 0.1) FROM test_tdigest_agg ORDER BY k'
).fetchall())
assert len(result) == 2
assert abs(int(result[0]['tdigest_quantile']) - 99) <= 1
assert abs(int(result[1]['tdigest_quantile']) - 599) <= 1
result = list(
octopus.execute(
'SELECT tdigest_quantile(combine(t), 0.1) FROM test_tdigest_agg').
fetchall())
assert len(result) == 1
assert abs(int(result[0]['tdigest_quantile']) - 200) <= 4
result = list(
octopus.execute(
'SELECT tdigest_cdf(t, 600) FROM test_tdigest_agg ORDER BY k').
fetchall())
assert len(result) == 2
assert round(result[0]['tdigest_cdf'], 2) == 0.6
assert round(result[1]['tdigest_cdf'], 2) == 0.1
result = list(
octopus.execute(
'SELECT tdigest_cdf(combine(t), 600) FROM test_tdigest_agg').
fetchall())
assert len(result) == 1
assert round(result[0]['tdigest_cdf'], 2) == 0.35
def test_multiple_insert(octopus, clean_db):
octopus.create_stream('stream0', x='int')
octopus.create_stream('stream1', x='int')
octopus.create_stream('stream2', x='int')
octopus.create_cv('cv0', 'SELECT count(*) FROM stream1')
octopus.create_cv('cv1', 'SELECT count(*) FROM stream2')
octopus.create_ct('ct1', 'SELECT x::int FROM stream0 WHERE mod(x, 2) = 0', "octopus_stream_insert('stream1', 'stream2')")
octopus.insert('stream0', ('x',), [(n,) for n in range(1000)])
count = octopus.execute('SELECT count FROM cv0').first()['count']
assert count == 500
count = octopus.execute('SELECT count FROM cv1').first()['count']
assert count == 500
def _test_hs_agg(octopus, agg):
values = [random.randint(-100, 100) for n in range(1000)]
h = random.choice(values) + random.randint(-10, 10)
octopus.create_stream('stream0', x='int')
cq = 'SELECT %s(%d) WITHIN GROUP (ORDER BY x::integer) FROM stream0' % (agg, h)
octopus.create_cv('test_%s' % agg, cq)
octopus.insert('stream0', ('x',), [(v,) for v in values])
result = octopus.execute('SELECT %s FROM test_%s' % (agg, agg)).first()
rank, peers = _rank(h, values)
dense_rank, _ = _dense_rank(h, values)
return rank, dense_rank, peers, len(values), result[agg]
def test_join_with_aggs(octopus, clean_db):
"""
Verify that joins involving aggregates referencing columns from
multiple tables work
"""
num_cols = 4
join_cols = [1]
q = """
SELECT
sum(s.col0::integer) AS s0,
sum(a0.col0::integer) AS s1,
sum(a1.col0::integer) AS s2
FROM a1 JOIN a0 ON a1.col1 = a0.col1
JOIN stream0 s ON s.col1::integer = a0.col1
"""
a0_cols = dict([('col%d' % n, 'integer') for n in range(num_cols)])
a1_cols = dict([('col%d' % n, 'integer') for n in range(num_cols)])
octopus.create_table('a0', **a0_cols)
octopus.create_table('a1', **a1_cols)
a0 = _generate_rows(num_cols, 64)
a1 = _generate_rows(num_cols, 64)
s = _generate_rows(num_cols, 64)
_insert(octopus, 'a0', a0, 0.1)
_insert(octopus, 'a1', a1, 0.1)
octopus.create_stream('stream0', **a0_cols)
octopus.create_cv('test_agg_join', q)
_insert(octopus, 'stream0', s)
expected = _join(a1, _join(a0, s, join_cols), join_cols)
result = octopus.execute('SELECT * FROM test_agg_join').first()
# sum of col0 from stream
s0_expected = sum([r[num_cols * 2] for r in expected])
# sum of col0 from a0
s1_expected = sum([r[num_cols * 1] for r in expected])
# sum of col0 from a1
s2_expected = sum([r[num_cols * 0] for r in expected])
assert s0_expected == result['s0']
assert s1_expected == result['s1']
assert s2_expected == result['s2']
def test_percentile_cont_agg(octopus, clean_db):
range_top = 100000
q = [0.0, 0.01, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.99, 1.0]
batches = []
min_seen = range_top
max_seen = 0
for _ in xrange(10):
b = [(random.randint(0, range_top), ) for _ in xrange(5000)]
min_seen = min(min_seen, min(b)[0])
max_seen = max(max_seen, max(b)[0])
batches.append(b)
octopus.create_stream('test_stream', x='int')
query = '''SELECT
percentile_cont(ARRAY[%s])
WITHIN GROUP (ORDER BY x::integer) FROM %s
''' % (', '.join(map(lambda f: str(f), q)), '%s')
octopus.create_cv('test_cq_percentile_cont', query % 'test_stream')
octopus.create_table('test_percentile_cont', x='integer')
for b in batches:
octopus.insert('test_stream', ('x', ), b)
octopus.insert('test_percentile_cont', ('x', ), b)
actual = octopus.execute(query % 'test_percentile_cont')
result = octopus.execute('SELECT * FROM test_cq_percentile_cont')
actual = actual.first()['percentile_cont']
result = result.first()['percentile_cont']
assert len(actual) == len(result)
assert result == sorted(result)
diff = [abs(actual[i] - result[i]) for i in xrange(len(actual))]
# 0th and 100th percentile should be accurate.
assert result[0] == min_seen
assert result[-1] == max_seen
# 1st and 99th percentile should be within 0.1%.
assert diff[1] <= 0.001 * range_top
assert diff[-2] <= 0.001 * range_top
# All percentiles should be within 0.5%.
assert all(x <= 0.005 * range_top for x in diff)
def test_concurrent_crash(octopus, clean_db):
"""
Test simple worker and combiner crashes.
"""
octopus.create_stream('stream0', x='int')
q = 'SELECT COUNT(*) FROM stream0'
octopus.create_cv('test_concurrent_crash', q)
batch_size = 25000
desc = [0, 0, False]
vals = [(1, )] * batch_size
def insert():
while True:
octopus.insert('stream0', ['x'], vals)
desc[1] += batch_size
if desc[2]:
break
def kill():
for _ in xrange(30):
r = random.random()
if r > 0.85:
desc[0] += kill_combiner()
if r < 0.15:
desc[0] += kill_worker()
time.sleep(0.1)
desc[2] = True
threads = [threading.Thread(target=insert), threading.Thread(target=kill)]
map(lambda t: t.start(), threads)
map(lambda t: t.join(), threads)
num_killed = desc[0]
num_inserted = desc[1]
result = octopus.execute('SELECT count FROM test_concurrent_crash').first()
assert num_killed > 0
assert result['count'] <= num_inserted
assert result['count'] >= num_inserted - (num_killed * batch_size)
# To ensure that all remaining events in ZMQ queues have been consumed
time.sleep(2)
def test_simple_insert(octopus, clean_db):
"""
Verify that we can insert some rows and count some stuff
"""
octopus.create_stream('stream0', key='int')
octopus.create_cv(
'cv', 'SELECT key::integer, COUNT(*) FROM stream0 GROUP BY key')
rows = [(n % 10, ) for n in range(1000)]
octopus.insert('stream0', ('key', ), rows)
result = list(octopus.execute('SELECT * FROM cv ORDER BY key'))
assert len(result) == 10
for i, row in enumerate(result):
assert row['key'] == i
assert row['count'] == 100
