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edges.py
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# Copyright (C) 2020 The Software Heritage developers
# See the AUTHORS file at the top-level directory of this distribution
# License: GNU General Public License version 3, or any later version
# See top-level LICENSE file for more information
import base64
import os
import os.path
import shlex
import subprocess
import tempfile
from typing import Tuple
from swh.dataset.exporter import ExporterDispatch
from swh.dataset.utils import ZSTFile, remove_pull_requests
from swh.model.hashutil import hash_to_hex
from swh.model.model import Origin
from swh.model.swhids import ExtendedObjectType
def swhid(object_type, object_id):
# We use string interpolation here instead of using ExtendedSWHID to format,
# as building temporary ExtendedSWHID objects has a non-negligeable impact
# on performance.
return f"swh:1:{object_type.value}:{hash_to_hex(object_id)}"
class GraphEdgesExporter(ExporterDispatch):
"""
Implementation of an exporter which writes all the graph edges
of a specific type to a Zstandard-compressed CSV file.
Each row of the CSV is in the format: ``<SRC SWHID> <DST SWHID>``.
"""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.writers = {}
def get_writers_for(self, obj_type: ExtendedObjectType):
if obj_type not in self.writers:
dataset_path = self.export_path / obj_type.name.lower()
dataset_path.mkdir(exist_ok=True)
unique_id = self.get_unique_file_id()
nodes_file = dataset_path / ("graph-{}.nodes.csv.zst".format(unique_id))
edges_file = dataset_path / ("graph-{}.edges.csv.zst".format(unique_id))
node_writer = self.exit_stack.enter_context(ZSTFile(str(nodes_file), "w"))
edge_writer = self.exit_stack.enter_context(ZSTFile(str(edges_file), "w"))
self.writers[obj_type] = (node_writer, edge_writer)
return self.writers[obj_type]
def get_node_writer_for(self, obj_type: ExtendedObjectType):
return self.get_writers_for(obj_type)[0]
def get_edge_writer_for(self, obj_type: ExtendedObjectType):
return self.get_writers_for(obj_type)[1]
def write_node(self, node: Tuple[ExtendedObjectType, bytes]):
node_type, node_id = node
if node_id is None:
return
node_swhid = swhid(object_type=node_type, object_id=node_id)
node_writer = self.get_node_writer_for(node_type)
node_writer.write("{}\n".format(node_swhid))
def write_edge(
self,
src: Tuple[ExtendedObjectType, bytes],
dst: Tuple[ExtendedObjectType, bytes],
*,
labels=None,
):
src_type, src_id = src
dst_type, dst_id = dst
if src_id is None or dst_id is None:
return
src_swhid = swhid(object_type=src_type, object_id=src_id)
dst_swhid = swhid(object_type=dst_type, object_id=dst_id)
edge_line = " ".join([src_swhid, dst_swhid] + (labels if labels else []))
edge_writer = self.get_edge_writer_for(src_type)
edge_writer.write("{}\n".format(edge_line))
def process_origin(self, origin):
origin_id = Origin(url=origin["url"]).id
self.write_node((ExtendedObjectType.ORIGIN, origin_id))
def process_origin_visit_status(self, visit_status):
origin_id = Origin(url=visit_status["origin"]).id
self.write_edge(
(ExtendedObjectType.ORIGIN, origin_id),
(ExtendedObjectType.SNAPSHOT, visit_status["snapshot"]),
)
def process_snapshot(self, snapshot):
if self.config.get("remove_pull_requests"):
remove_pull_requests(snapshot)
self.write_node((ExtendedObjectType.SNAPSHOT, snapshot["id"]))
for branch_name, branch in snapshot["branches"].items():
original_branch_name = branch_name
while branch and branch.get("target_type") == "alias":
branch_name = branch["target"]
branch = snapshot["branches"].get(branch_name)
if branch is None or not branch_name:
continue
self.write_edge(
(ExtendedObjectType.SNAPSHOT, snapshot["id"]),
(ExtendedObjectType[branch["target_type"].upper()], branch["target"]),
labels=[
base64.b64encode(original_branch_name).decode(),
],
)
def process_release(self, release):
self.write_node((ExtendedObjectType.RELEASE, release["id"]))
self.write_edge(
(ExtendedObjectType.RELEASE, release["id"]),
(ExtendedObjectType[release["target_type"].upper()], release["target"]),
)
def process_revision(self, revision):
self.write_node((ExtendedObjectType.REVISION, revision["id"]))
self.write_edge(
(ExtendedObjectType.REVISION, revision["id"]),
(ExtendedObjectType.DIRECTORY, revision["directory"]),
)
for parent in revision["parents"]:
self.write_edge(
(ExtendedObjectType.REVISION, revision["id"]),
(ExtendedObjectType.REVISION, parent),
)
def process_directory(self, directory):
self.write_node((ExtendedObjectType.DIRECTORY, directory["id"]))
for entry in directory["entries"]:
entry_type_mapping = {
"file": ExtendedObjectType.CONTENT,
"dir": ExtendedObjectType.DIRECTORY,
"rev": ExtendedObjectType.REVISION,
}
self.write_edge(
(ExtendedObjectType.DIRECTORY, directory["id"]),
(entry_type_mapping[entry["type"]], entry["target"]),
labels=[base64.b64encode(entry["name"]).decode(), str(entry["perms"])],
)
def process_content(self, content):
self.write_node((ExtendedObjectType.CONTENT, content["sha1_git"]))
def sort_graph_nodes(export_path, config):
"""
Generate the node list from the edges files.
We cannot solely rely on the object IDs that are read in the journal,
as some nodes that are referred to as destinations in the edge file
might not be present in the archive (e.g a rev_entry referring to a
revision that we do not have crawled yet).
The most efficient way of getting all the nodes that are mentioned in
the edges file is therefore to use sort(1) on the gigantic edge files
to get all the unique node IDs, while using the disk as a temporary
buffer.
This pipeline does, in order:
- concatenate and write all the compressed edges files in
graph.edges.csv.zst (using the fact that ZST compression is an additive
function) ;
- deflate the edges ;
- count the number of edges and write it in graph.edges.count.txt ;
- count the number of occurrences of each edge type and write them
in graph.edges.stats.txt ;
- concatenate all the (deflated) nodes from the export with the
destination edges, and sort the output to get the list of unique graph
nodes ;
- count the number of unique graph nodes and write it in
graph.nodes.count.txt ;
- count the number of occurrences of each node type and write them
in graph.nodes.stats.txt ;
- compress and write the resulting nodes in graph.nodes.csv.zst.
"""
# Use awk as a replacement of `sort | uniq -c` to avoid buffering everything
# in memory
counter_command = "awk '{ t[$0]++ } END { for (i in t) print i,t[i] }'"
sort_script = """
pv {export_path}/*/*.edges.csv.zst |
tee {export_path}/graph.edges.csv.zst |
zstdcat |
tee >( wc -l > {export_path}/graph.edges.count.txt ) |
tee >( cut -d: -f3,6 | {counter_command} | sort \
> {export_path}/graph.edges.stats.txt ) |
tee >( cut -d' ' -f3 | grep . | \
sort -u -S{sort_buffer_size} -T{buffer_path} | \
zstdmt > {export_path}/graph.labels.csv.zst ) |
cut -d' ' -f2 |
cat - <( zstdcat {export_path}/*/*.nodes.csv.zst ) |
sort -u -S{sort_buffer_size} -T{buffer_path} |
tee >( wc -l > {export_path}/graph.nodes.count.txt ) |
tee >( cut -d: -f3 | {counter_command} | sort \
> {export_path}/graph.nodes.stats.txt ) |
zstdmt > {export_path}/graph.nodes.csv.zst
"""
# Use bytes for the sorting algorithm (faster than being locale-specific)
env = {
**os.environ.copy(),
"LC_ALL": "C",
"LC_COLLATE": "C",
"LANG": "C",
}
sort_buffer_size = config.get("sort_buffer_size", "4G")
disk_buffer_dir = config.get("disk_buffer_dir", export_path)
with tempfile.TemporaryDirectory(
prefix=".graph_node_sort_", dir=disk_buffer_dir
) as buffer_path:
subprocess.run(
[
"bash",
"-c",
sort_script.format(
export_path=shlex.quote(str(export_path)),
buffer_path=shlex.quote(str(buffer_path)),
sort_buffer_size=shlex.quote(sort_buffer_size),
counter_command=counter_command,
),
],
env=env,
)

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