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Posted to dev@sedona.apache.org by "Doug Dennis (Jira)" <ji...@apache.org> on 2023/01/01 09:19:00 UTC
[jira] [Created] (SEDONA-227) Python SerDe Performance Degradation
Doug Dennis created SEDONA-227:
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Summary: Python SerDe Performance Degradation
Key: SEDONA-227
URL: https://issues.apache.org/jira/browse/SEDONA-227
Project: Apache Sedona
Issue Type: Bug
Reporter: Doug Dennis
With the new geometry serde in Sedona, there appears to be a fairly significant performance regression on the python side. The PR's author acknowledged a regression in the PR so this is expected, however my trials are showing a regression that is sometimes far higher than the 2x noted in the PR.
For serialization, I'm seeing points and short linestrings taking about twice as long (as expected). Unfortunately, small polygons are taking about 7-8 times longer while long linestrings and large polygons are taking between 11-12 times longer.
The news isn't all bad though. For me, short linestrings are consistently deserializing faster (about 25-30% faster) and points are deserializing at roughly the same rate as before. The other deserializations show regressions that are more or less in line with the results for serialization though.
To test this, I'm strictly comparing the new serialize and deserialize sedona functions against shapely's wkb loads and dumps functions. Below you will find my most recent results (which have been fairly consistent) as well as the python code I used to generate it. I'm very open to critiques of my approach to measuring performance, and hope that some of this performance loss is due to my own error.
Serialization results:
{code:java}
short line serialize trial:
Total Time (seconds):
Shapely: 1.7364926
Sedona: 5.4626863
Factor: 2.145816054730092
Average Time (nanoseconds):
Shapely: 8682.463
Sedona: 27313.4315
Factor: 2.145816054730092
long line serialize trial:
Total Time (seconds):
Shapely: 4.0879395
Sedona: 50.1508444
Factor: 11.268000639441949
Average Time (nanoseconds):
Shapely: 40879.395
Sedona: 501508.444
Factor: 11.268000639441949
point serialize trial:
Total Time (seconds):
Shapely: 4.7864782
Sedona: 13.0319586
Factor: 1.7226612251153677
Average Time (nanoseconds):
Shapely: 9572.9564
Sedona: 26063.9172
Factor: 1.7226612251153677
small polygon serialize trial:
Total Time (seconds):
Shapely: 1.8339082
Sedona: 14.9376628
Factor: 7.145262014750793
Average Time (nanoseconds):
Shapely: 9169.541
Sedona: 74688.314
Factor: 7.145262014750793
large polygon serialize trial:
Total Time (seconds):
Shapely: 2.3705298
Sedona: 30.4154897
Factor: 11.830671734225826
Average Time (nanoseconds):
Shapely: 23705.298
Sedona: 304154.897
Factor: 11.830671734225826 {code}
Deserialization results:
{code:java}
short line deserialize trial:
Total Time (seconds):
Shapely: 2.5166469
Sedona: 1.7909991
Factor: -0.28833913887562057
Average Time (nanoseconds):
Shapely: 12583.2345
Sedona: 8954.9955
Factor: -0.28833913887562057
long line deserialize trial:
Total Time (seconds):
Shapely: 3.1818201
Sedona: 45.1792348
Factor: 13.199179519923204
Average Time (nanoseconds):
Shapely: 31818.201
Sedona: 451792.348
Factor: 13.199179519923204
point deserialize trial:
Total Time (seconds):
Shapely: 5.7874722
Sedona: 5.3168965
Factor: -0.08130936680784402
Average Time (nanoseconds):
Shapely: 11574.9444
Sedona: 10633.793
Factor: -0.08130936680784402
small polygon deserialize trial:
Total Time (seconds):
Shapely: 2.5079775
Sedona: 4.0216245
Factor: 0.6035329264317563
Average Time (nanoseconds):
Shapely: 12539.8875
Sedona: 20108.1225
Factor: 0.6035329264317563
large polygon deserialize trial:
Total Time (seconds):
Shapely: 1.9952702
Sedona: 19.909025
Factor: 8.978109731704508
Average Time (nanoseconds):
Shapely: 19952.702
Sedona: 199090.25
Factor: 8.978109731704508 {code}
Python code used to generate results:
{code:java}
from sedona.utils.geometry_serde import serialize, deserialize
from shapely.geometry import LineString, Point, Polygon
from shapely.wkb import dumps, loads
import time
def run_serialize_trial(geom, number_iterations, name):
print(f"{name} serialize trial:")
start_time = time.perf_counter_ns()
for _ in range(number_iterations):
dumps(geom)
shapely_time = time.perf_counter_ns() - start_time
start_time = time.perf_counter_ns()
for _ in range(number_iterations):
serialize(geom)
sedona_time = time.perf_counter_ns() - start_time
print(f"\tTotal Time (seconds):")
print(f"\t\tShapely: {shapely_time / 1e9}\n\t\tSedona: {sedona_time / 1e9}\n\t\tFactor: {(sedona_time - shapely_time) / shapely_time}\n")
print(f"\tAverage Time (nanoseconds):")
print(f"\t\tShapely: {shapely_time / number_iterations}\n\t\tSedona: {sedona_time / number_iterations}\n\t\tFactor: {(sedona_time - shapely_time) / shapely_time}\n")
def run_deserialize_trial(geom, number_iterations, name):
print(f"{name} deserialize trial:")
shapely_serialized_geom = dumps(geom)
sedona_serialized_geom = serialize(geom)
start_time = time.perf_counter_ns()
for _ in range(number_iterations):
loads(shapely_serialized_geom)
shapely_time = time.perf_counter_ns() - start_time
start_time = time.perf_counter_ns()
for _ in range(number_iterations):
deserialize(sedona_serialized_geom)
sedona_time = time.perf_counter_ns() - start_time
print(f"\tTotal Time (seconds):")
print(f"\t\tShapely: {shapely_time / 1e9}\n\t\tSedona: {sedona_time / 1e9}\n\t\tFactor: {(sedona_time - shapely_time) / shapely_time}\n")
print(f"\tAverage Time (nanoseconds):")
print(f"\t\tShapely: {shapely_time / number_iterations}\n\t\tSedona: {sedona_time / number_iterations}\n\t\tFactor: {(sedona_time - shapely_time) / shapely_time}\n")
short_line_iterations = 200_000
short_line = LineString([(10.0, 10.0), (20.0, 20.0)])
long_line_iterations = 100_000
long_line = LineString([(float(n), float(n)) for n in range(1000)])
point_iterations = 500_000
point = Point(12.3, 45.6)
small_polygon_iterations = 200_000
small_polygon = Polygon([(10.0, 10.0), (20.0, 10.0), (20.0, 20.0), (10.0, 20.0), (10.0, 10.0)])
large_polygon_iterations = 100_000
large_polygon = Polygon(
[(0.0, float(n * 10)) for n in range(100)]
+ [(float(n * 10), 990.0) for n in range(100)]
+ [(990.0, float(n * 10)) for n in reversed(range(100))]
+ [(float(n * 10), 0.0) for n in reversed(range(100))]
)
run_serialize_trial(short_line, short_line_iterations, "short line")
run_serialize_trial(long_line, long_line_iterations, "long line")
run_serialize_trial(point, point_iterations, "point")
run_serialize_trial(small_polygon, small_polygon_iterations, "small polygon")
run_serialize_trial(large_polygon, large_polygon_iterations, "large polygon")
run_deserialize_trial(short_line, short_line_iterations, "short line")
run_deserialize_trial(long_line, long_line_iterations, "long line")
run_deserialize_trial(point, point_iterations, "point")
run_deserialize_trial(small_polygon, small_polygon_iterations, "small polygon")
run_deserialize_trial(large_polygon, large_polygon_iterations, "large polygon"){code}
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