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Wes McKinney
8c21776022
These benchmarks will help track possible regressions in buffered IO performance from the Python side. This also allows objects that implement the right APIs (at least according to `hasattr`) to be passed into these functions. Closes #5356 from wesm/ARROW-4220 and squashes the following commits:0307cd919<Wes McKinney> Code reviewbba2aa62c<Wes McKinney> Add buffered IO benchmarks with simulated high latency Authored-by: Wes McKinney <wesm+git@apache.org> Signed-off-by: Wes McKinney <wesm+git@apache.org>
90 lines
2.6 KiB
Python
90 lines
2.6 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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import time
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import pyarrow as pa
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class HighLatencyReader(object):
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def __init__(self, raw, latency):
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self.raw = raw
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self.latency = latency
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def close(self):
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self.raw.close()
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@property
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def closed(self):
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return self.raw.closed
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def read(self, nbytes=None):
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time.sleep(self.latency)
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return self.raw.read(nbytes)
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class HighLatencyWriter(object):
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def __init__(self, raw, latency):
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self.raw = raw
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self.latency = latency
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def close(self):
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self.raw.close()
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@property
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def closed(self):
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return self.raw.closed
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def write(self, data):
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time.sleep(self.latency)
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self.raw.write(data)
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class BufferedIOHighLatency(object):
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"""Benchmark creating a parquet manifest."""
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increment = 1024
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total_size = 16 * (1 << 20) # 16 MB
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buffer_size = 1 << 20 # 1 MB
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latency = 0.1 # 100ms
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param_names = ('latency',)
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params = [0, 0.01, 0.1]
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def time_buffered_writes(self, latency):
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test_data = b'x' * self.increment
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bytes_written = 0
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out = pa.BufferOutputStream()
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slow_out = HighLatencyWriter(out, latency)
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buffered_out = pa.output_stream(slow_out, buffer_size=self.buffer_size)
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while bytes_written < self.total_size:
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buffered_out.write(test_data)
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bytes_written += self.increment
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buffered_out.flush()
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def time_buffered_reads(self, latency):
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bytes_read = 0
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reader = pa.input_stream(pa.py_buffer(b'x' * self.total_size))
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slow_reader = HighLatencyReader(reader, latency)
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buffered_reader = pa.input_stream(slow_reader,
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buffer_size=self.buffer_size)
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while bytes_read < self.total_size:
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buffered_reader.read(self.increment)
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bytes_read += self.increment
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