def run_generator():
generate_search_blocks.main(
db_factory(),
search_strategy=SuperabundantSearchStrategy(),
# this ensures there are many blocks that are quick
# to process, maximizing the likelihood of a
# conflict. For example, this test will fail if the
# 'FOR UPDATE' is removed from the subquery in
# claim_next_search_block
args=FakeArgs(refresh_count=10000, block_size=2))
def test_superabundant_exactly_landing_on_level_boundary():
search = SuperabundantSearchStrategy().starting_from(
SuperabundantEnumerationIndex(level=4, index_in_level=1))
'''
The parititions of 4 are
[[4], [3, 1], [2, 2], [2, 1, 1], [1, 1, 1, 1]]
So if the index in the level is 1, a batch size of 4 should land
exactly on the boundary of the level.
'''
blocks = search.generate_search_blocks(count=2, batch_size=4)
assert blocks[0].starting_search_index == SuperabundantEnumerationIndex(
level=4, index_in_level=1)
assert blocks[0].ending_search_index == SuperabundantEnumerationIndex(
level=4, index_in_level=4)
assert blocks[1].starting_search_index == SuperabundantEnumerationIndex(
level=5, index_in_level=0)
assert blocks[1].ending_search_index == SuperabundantEnumerationIndex(
level=5, index_in_level=3)
from riemann.search_strategy import SuperabundantSearchStrategy
from riemann.types import SuperabundantEnumerationIndex
import tracemalloc
tracemalloc.start()
search_strategy = SuperabundantSearchStrategy().starting_from(
SuperabundantEnumerationIndex(71, 196047))
batch = search_strategy.next_batch(250000)
snapshot = tracemalloc.take_snapshot()
top_stats = snapshot.statistics('lineno')
print("[ Top 10 ]")
for stat in top_stats[:10]:
print(stat)
def run_processor():
process_search_blocks.main(
db_factory(), search_strategy=SuperabundantSearchStrategy())
def run_generator():
generate_search_blocks.main(
db_factory(),
search_strategy=SuperabundantSearchStrategy(),
args=FakeArgs())
def index_name(self) -> str:
return SuperabundantSearchStrategy().index_name()