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Creates PoC pipeline to estimate disk usage of vcf_to_bq on Dataflow.
The pipeline uses raw file size and raw+encoded sizes of a short snippet at beginning of VCF files to estimate the encoded size for a commit. The major blocking bug is that when the snippets are being read from VCFs in an encoded format, lines are being read more than once.
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| # Copyright 2018 Google Inc. All Rights Reserved. | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
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| """A source for estimating the size of VCF files when processed by vcf_to_bq.""" | ||
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| from __future__ import absolute_import | ||
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| from typing import Iterable, List, Tuple # pylint: disable=unused-import | ||
| import logging | ||
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| import apache_beam as beam | ||
| from apache_beam import coders | ||
| from apache_beam import transforms | ||
| from apache_beam.io import filebasedsource | ||
| from apache_beam.io import range_trackers # pylint: disable=unused-import | ||
| from apache_beam.io import filesystem | ||
| from apache_beam.io import filesystems | ||
| from apache_beam.io import iobase | ||
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| from gcp_variant_transforms.beam_io import vcfio | ||
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| def _get_file_sizes(file_pattern): | ||
| # type: (str) -> List[FileSizeInfo] | ||
| file_sizes = [] | ||
| match_result = filesystems.FileSystems.match([file_pattern])[0] | ||
| for file_metadata in match_result.metadata_list: | ||
| compression_type = filesystem.CompressionTypes.detect_compression_type( | ||
| file_metadata.path) | ||
| if compression_type != filesystem.CompressionTypes.UNCOMPRESSED: | ||
| logging.error("VCF file %s is compressed; disk requirement estimator " | ||
| "will not be accurate.", file_metadata.path) | ||
| file_sizes.append((file_metadata.path, file_metadata.size_in_bytes,)) | ||
| return file_sizes | ||
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| def _convert_variants_to_bytesize(variant): | ||
| # type: (vcfio.Variant) -> int | ||
| return coders.registry.get_coder(vcfio.Variant).estimate_size(variant) | ||
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| class FileSizeInfo(object): | ||
| def __init__(self, name, raw_file_size, encoded_file_size=None): | ||
| # type: (str, int, int) -> None | ||
| self.name = name | ||
| self.raw_size = raw_file_size | ||
| self.encoded_size = encoded_file_size # Optional, useful for SumFn. | ||
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| def estimate_encoded_file_size(self, raw_sample_size, encoded_sample_size): | ||
| # type: (int, int) -> None | ||
| """Estimates a VCF file's encoded (byte) size by analyzing sample Variants. | ||
| Given the raw_file_size and measurements of several VCF lines from the file, | ||
| estimate how much disk the file will take after expansion due to encoding | ||
| lines as `vcfio.Variant` objects. The encoded_sample_size will be set as | ||
| `self.encoded`. | ||
| This is a simple ratio problem, solving for encoded_sample_size which is | ||
| the only unknown: | ||
| encoded_sample_size / raw_sample_size = encoded_file_size / raw_file_size | ||
| """ | ||
| if raw_sample_size == 0: | ||
| # Propagate in-band error state to avoid divide-by-zero. | ||
| logging.warning("File %s appears to have no valid Variant lines. File " | ||
| "will be ignored for size estimation.", self.name) | ||
| self.encoded_size = 0 | ||
| self.raw_size = 0 | ||
| else: | ||
| self.encoded_size = (self.raw_size * encoded_sample_size / | ||
| raw_sample_size) | ||
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| class FileSizeInfoSumFn(beam.CombineFn): | ||
| """Combiner Function to sum up the size fields of FileSizeInfo objects. | ||
| Unlike VariantsSizeInfoSumFn, the input is a PTable mapping str to | ||
| FileSizeInfo, so the input is a tuple with the FileSizeInfos as the second | ||
| field. The output strips out the str key which represents the file path. | ||
| Example: [FileSizeInfo(a, b), FileSizeInfo(c, d)] -> FileSizeInfo(a+c, b+d) | ||
| """ | ||
| def create_accumulator(self): | ||
| # type: (None) -> Tuple[int, int] | ||
| return (0, 0) # (raw, encoded) sums | ||
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| def add_input(self, (raw, encoded), file_size_info): | ||
| # type: (Tuple[int, int], FileSizeInfo) -> Tuple[int, int] | ||
| return raw + file_size_info.raw_size, encoded + file_size_info.encoded_size | ||
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| def merge_accumulators(self, accumulators): | ||
| # type: (Iterable[Tuple[int, int]]) -> Tuple[int, int] | ||
| raw, encoded = zip(*accumulators) | ||
| return sum(raw), sum(encoded) | ||
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| def extract_output(self, (raw, encoded)): | ||
| # type: (Tuple[int, int]) -> FileSizeInfo | ||
| return FileSizeInfo("cumulative", raw, encoded) | ||
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| class _EstimateVcfSizeSource(filebasedsource.FileBasedSource): | ||
| """A source for estimating the encoded size of a VCF file in `vcf_to_bq`. | ||
| This source first reads a limited number of variants from a set of VCF files, | ||
| then | ||
| Lines that are malformed are skipped. | ||
| Parses VCF files (version 4) using PyVCF library. | ||
| """ | ||
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| DEFAULT_VCF_READ_BUFFER_SIZE = 65536 # 64kB | ||
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| def __init__(self, | ||
| file_pattern, | ||
| sample_size, | ||
| compression_type=filesystem.CompressionTypes.AUTO, | ||
| validate=True, | ||
| vcf_parser_type=vcfio.VcfParserType.PYVCF): | ||
| # type: (str, int, str, bool, vcfio.VcfParserType) -> None | ||
| super(_EstimateVcfSizeSource, self).__init__( | ||
| file_pattern, | ||
| compression_type=compression_type, | ||
| validate=validate, | ||
| splittable=False) | ||
| self._compression_type = compression_type | ||
| self._sample_size = sample_size | ||
| self._vcf_parser_type = vcf_parser_type | ||
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| def read_records( | ||
| self, | ||
| file_name, # type: str | ||
| range_tracker # type: range_trackers.UnsplittableRangeTracker | ||
| ): | ||
| # type: (...) -> Iterable[Tuple[str, str, vcfio.Variant]] | ||
| """Iterator to emit lines encoded as `Variant` objects.""" | ||
| vcf_parser_class = vcfio.get_vcf_parser(self._vcf_parser_type) | ||
| record_iterator = vcf_parser_class( | ||
| file_name, | ||
| range_tracker, | ||
| self._pattern, | ||
| self._compression_type, | ||
| allow_malformed_records=True, | ||
| representative_header_lines=None, | ||
| buffer_size=self.DEFAULT_VCF_READ_BUFFER_SIZE, | ||
| skip_header_lines=0) | ||
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| _, raw_file_size = _get_file_sizes(file_name)[0] | ||
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| # Open distinct channel to read lines as raw bytestrings. | ||
| with filesystems.FileSystems.open(file_name, | ||
| self._compression_type) as raw_reader: | ||
| raw_record = raw_reader.readline() | ||
| while raw_record and raw_record.startswith('#'): | ||
| # Skip headers, assume header size is negligible. | ||
| raw_record = raw_reader.readline() | ||
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| count, raw_size, encoded_size = 0, 0, 0 | ||
| for encoded_record in record_iterator: | ||
| if count >= self._sample_size: | ||
| break | ||
| if not isinstance(encoded_record, vcfio.Variant): | ||
| logging.error( | ||
| "Skipping VCF line that could not be decoded as a " | ||
| "`vcfio.Variant` in file %s: %s", file_name, raw_record) | ||
| continue | ||
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| raw_size += len(raw_record) | ||
| encoded_size += _convert_variants_to_bytesize(encoded_record) | ||
| count += 1 | ||
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| raw_record = raw_reader.readline() # Increment raw iterator. | ||
| file_size_info = FileSizeInfo(file_name, raw_file_size) | ||
| file_size_info.estimate_encoded_file_size(raw_size, encoded_size) | ||
| yield file_size_info | ||
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| class EstimateVcfSize(transforms.PTransform): | ||
| """A PTransform for reading a limited number of lines from a set of VCF files. | ||
| Output will be a PTable mapping from `file names -> Tuple[(line, Variant)]` | ||
| objects. The list contains the first `sample_size` number of lines that are | ||
| not malformed, first as a raw string and then encoded as a `Variant` class. | ||
| Parses VCF files (version 4) using PyVCF library. | ||
| """ | ||
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| def __init__( | ||
| self, | ||
| file_pattern, # type: str | ||
| sample_size, # type: int | ||
| compression_type=filesystem.CompressionTypes.AUTO, # type: str | ||
| validate=True, # type: bool | ||
| **kwargs # type: **str | ||
| ): | ||
| # type: (...) -> None | ||
| """Initialize the :class:`ReadVcfHeaders` transform. | ||
| Args: | ||
| file_pattern: The file path to read from either as a single file or a glob | ||
| pattern. | ||
| sample_size: The number of lines that should be read from the file. | ||
| compression_type: Used to handle compressed input files. | ||
| Typical value is :attr:`CompressionTypes.AUTO | ||
| <apache_beam.io.filesystem.CompressionTypes.AUTO>`, in which case the | ||
| underlying file_path's extension will be used to detect the compression. | ||
| validate: Flag to verify that the files exist during the pipeline creation | ||
| time. | ||
| """ | ||
| super(EstimateVcfSize, self).__init__(**kwargs) | ||
| self._source = _EstimateVcfSizeSource( | ||
| file_pattern, sample_size, compression_type, validate=validate) | ||
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| def expand(self, pvalue): | ||
| return pvalue.pipeline | iobase.Read(self._source) |
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