Page MenuHomeSoftware Heritage
Files F9342445

indexer.py
No OneTemporary
Actions

indexer.py
View Options

# Copyright (C) 2016-2018 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 abc
import ast
import os
import logging
import shutil
import tempfile
import datetime
from copy import deepcopy
from contextlib import contextmanager
from swh.scheduler import get_scheduler
from swh.storage import get_storage
from swh.core.config import SWHConfig
from swh.objstorage import get_objstorage
from swh.objstorage.exc import ObjNotFoundError
from swh.indexer.storage import get_indexer_storage, INDEXER_CFG_KEY
from swh.model import hashutil
from swh.core import utils
@contextmanager
def write_to_temp(filename, data, working_directory):
"""Write the sha1's content in a temporary file.
Args:
filename (str): one of sha1's many filenames
data (bytes): the sha1's content to write in temporary
file
Returns:
The path to the temporary file created. That file is
filled in with the raw content's data.
"""
os.makedirs(working_directory, exist_ok=True)
temp_dir = tempfile.mkdtemp(dir=working_directory)
content_path = os.path.join(temp_dir, filename)
with open(content_path, 'wb') as f:
f.write(data)
yield content_path
shutil.rmtree(temp_dir)
class BaseIndexer(SWHConfig, metaclass=abc.ABCMeta):
"""Base class for indexers to inherit from.
The main entry point is the :func:`run` function which is in
charge of triggering the computations on the batch dict/ids
received.
Indexers can:
- filter out ids whose data has already been indexed.
- retrieve ids data from storage or objstorage
- index this data depending on the object and store the result in
storage.
To implement a new object type indexer, inherit from the
BaseIndexer and implement indexing:
:meth:`~BaseIndexer.run`:
object_ids are different depending on object. For example: sha1 for
content, sha1_git for revision, directory, release, and id for origin
To implement a new concrete indexer, inherit from the object level
classes: :class:`ContentIndexer`, :class:`RevisionIndexer`,
:class:`OriginIndexer`.
Then you need to implement the following functions:
:meth:`~BaseIndexer.filter`:
filter out data already indexed (in storage).
:meth:`~BaseIndexer.index_object`:
compute index on id with data (retrieved from the storage or the
objstorage by the id key) and return the resulting index computation.
:meth:`~BaseIndexer.persist_index_computations`:
persist the results of multiple index computations in the storage.
The new indexer implementation can also override the following functions:
:meth:`~BaseIndexer.prepare`:
Configuration preparation for the indexer. When overriding, this must
call the `super().prepare()` instruction.
:meth:`~BaseIndexer.check`:
Configuration check for the indexer. When overriding, this must call the
`super().check()` instruction.
:meth:`~BaseIndexer.register_tools`:
This should return a dict of the tool(s) to use when indexing or
filtering.
"""
CONFIG = 'indexer/base'
DEFAULT_CONFIG = {
INDEXER_CFG_KEY: ('dict', {
'cls': 'remote',
'args': {
'url': 'http://localhost:5007/'
}
}),
'storage': ('dict', {
'cls': 'remote',
'args': {
'url': 'http://localhost:5002/',
}
}),
'objstorage': ('dict', {
'cls': 'remote',
'args': {
'url': 'http://localhost:5003/',
}
})
}
ADDITIONAL_CONFIG = {}
USE_TOOLS = True
def __init__(self, config=None, **kw):
"""Prepare and check that the indexer is ready to run.
"""
super().__init__()
if config is not None:
self.config = config
else:
config_keys = ('base_filename', 'config_filename',
'additional_configs', 'global_config')
config_args = {k: v for k, v in kw.items() if k in config_keys}
if self.ADDITIONAL_CONFIG:
config_args.setdefault('additional_configs', []).append(
self.ADDITIONAL_CONFIG)
self.config = self.parse_config_file(**config_args)
self.prepare()
self.check()
self.log.debug('%s: config=%s', self, self.config)
def prepare(self):
"""Prepare the indexer's needed runtime configuration.
Without this step, the indexer cannot possibly run.
"""
config_storage = self.config.get('storage')
if config_storage:
self.storage = get_storage(**config_storage)
objstorage = self.config['objstorage']
self.objstorage = get_objstorage(objstorage['cls'],
objstorage['args'])
idx_storage = self.config[INDEXER_CFG_KEY]
self.idx_storage = get_indexer_storage(**idx_storage)
_log = logging.getLogger('requests.packages.urllib3.connectionpool')
_log.setLevel(logging.WARN)
self.log = logging.getLogger('swh.indexer')
if self.USE_TOOLS:
self.tools = list(self.register_tools(
self.config.get('tools', [])))
self.results = []
@property
def tool(self):
return self.tools[0]
def check(self):
"""Check the indexer's configuration is ok before proceeding.
If ok, does nothing. If not raise error.
"""
if self.USE_TOOLS and not self.tools:
raise ValueError('Tools %s is unknown, cannot continue' %
self.tools)
def _prepare_tool(self, tool):
"""Prepare the tool dict to be compliant with the storage api.
"""
return {'tool_%s' % key: value for key, value in tool.items()}
def register_tools(self, tools):
"""Permit to register tools to the storage.
Add a sensible default which can be overridden if not
sufficient. (For now, all indexers use only one tool)
Expects the self.config['tools'] property to be set with
one or more tools.
Args:
tools (dict/[dict]): Either a dict or a list of dict.
Returns:
list: List of dicts with additional id key.
Raises:
ValueError: if not a list nor a dict.
"""
if isinstance(tools, list):
tools = list(map(self._prepare_tool, tools))
elif isinstance(tools, dict):
tools = [self._prepare_tool(tools)]
else:
raise ValueError('Configuration tool(s) must be a dict or list!')
if tools:
return self.idx_storage.indexer_configuration_add(tools)
else:
return []
def index(self, id, data):
"""Index computation for the id and associated raw data.
Args:
id (bytes): identifier
data (bytes): id's data from storage or objstorage depending on
object type
Returns:
dict: a dict that makes sense for the
:meth:`.persist_index_computations` method.
"""
raise NotImplementedError()
def filter(self, ids):
"""Filter missing ids for that particular indexer.
Args:
ids ([bytes]): list of ids
Yields:
iterator of missing ids
"""
yield from ids
@abc.abstractmethod
def persist_index_computations(self, results, policy_update):
"""Persist the computation resulting from the index.
Args:
results ([result]): List of results. One result is the
result of the index function.
policy_update ([str]): either 'update-dups' or 'ignore-dups' to
respectively update duplicates or ignore them
Returns:
None
"""
pass
def next_step(self, results, task):
"""Do something else with computations results (e.g. send to another
queue, ...).
(This is not an abstractmethod since it is optional).
Args:
results ([result]): List of results (dict) as returned
by index function.
task (dict): a dict in the form expected by
`scheduler.backend.SchedulerBackend.create_tasks`
without `next_run`, plus an optional `result_name` key.
Returns:
None
"""
if task:
if getattr(self, 'scheduler', None):
scheduler = self.scheduler
else:
scheduler = get_scheduler(**self.config['scheduler'])
task = deepcopy(task)
result_name = task.pop('result_name', None)
task['next_run'] = datetime.datetime.now()
if result_name:
task['arguments']['kwargs'][result_name] = self.results
scheduler.create_tasks([task])
@abc.abstractmethod
def run(self, ids, policy_update,
next_step=None, **kwargs):
"""Given a list of ids:
- retrieves the data from the storage
- executes the indexing computations
- stores the results (according to policy_update)
Args:
ids ([bytes]): id's identifier list
policy_update (str): either 'update-dups' or 'ignore-dups' to
respectively update duplicates or ignore them
next_step (dict): a dict in the form expected by
`scheduler.backend.SchedulerBackend.create_tasks`
without `next_run`, plus a `result_name` key.
**kwargs: passed to the `index` method
"""
pass
class ContentIndexer(BaseIndexer):
"""A content indexer working on a list of ids directly.
To work on indexer range, use the :class:`ContentRangeIndexer`
instead.
Note: :class:`ContentIndexer` is not an instantiable object. To
use it, one should inherit from this class and override the
methods mentioned in the :class:`BaseIndexer` class.
"""
def run(self, ids, policy_update,
next_step=None, **kwargs):
"""Given a list of ids:
- retrieve the content from the storage
- execute the indexing computations
- store the results (according to policy_update)
Args:
ids (Iterable[Union[bytes, str]]): sha1's identifier list
policy_update (str): either 'update-dups' or 'ignore-dups' to
respectively update duplicates or ignore
them
next_step (dict): a dict in the form expected by
`scheduler.backend.SchedulerBackend.create_tasks`
without `next_run`, plus an optional `result_name` key.
**kwargs: passed to the `index` method
"""
ids = [hashutil.hash_to_bytes(id_) if isinstance(id_, str) else id_
for id_ in ids]
results = []
try:
for sha1 in ids:
try:
raw_content = self.objstorage.get(sha1)
except ObjNotFoundError:
self.log.warning('Content %s not found in objstorage' %
hashutil.hash_to_hex(sha1))
continue
res = self.index(sha1, raw_content, **kwargs)
if res: # If no results, skip it
results.append(res)
self.persist_index_computations(results, policy_update)
self.results = results
return self.next_step(results, task=next_step)
except Exception:
self.log.exception(
'Problem when reading contents metadata.')
class ContentRangeIndexer(BaseIndexer):
"""A content range indexer.
This expects as input a range of ids to index.
To work on a list of ids, use the :class:`ContentIndexer` instead.
Note: :class:`ContentRangeIndexer` is not an instantiable
object. To use it, one should inherit from this class and override
the methods mentioned in the :class:`BaseIndexer` class.
"""
@abc.abstractmethod
def indexed_contents_in_range(self, start, end):
"""Retrieve indexed contents within range [start, end].
Args:
start (bytes): Starting bound from range identifier
end (bytes): End range identifier
Yields:
bytes: Content identifier present in the range ``[start, end]``
"""
pass
def _list_contents_to_index(self, start, end, indexed):
"""Compute from storage the new contents to index in the range [start,
end]. The already indexed contents are skipped.
Args:
start (bytes): Starting bound from range identifier
end (bytes): End range identifier
indexed (Set[bytes]): Set of content already indexed.
Yields:
bytes: Identifier of contents to index.
"""
if not isinstance(start, bytes) or not isinstance(end, bytes):
raise TypeError('identifiers must be bytes, not %r and %r.' %
(start, end))
while start:
result = self.storage.content_get_range(start, end)
contents = result['contents']
for c in contents:
_id = hashutil.hash_to_bytes(c['sha1'])
if _id in indexed:
continue
yield _id
start = result['next']
def _index_contents(self, start, end, indexed, **kwargs):
"""Index the contents from within range [start, end]
Args:
start (bytes): Starting bound from range identifier
end (bytes): End range identifier
indexed (Set[bytes]): Set of content already indexed.
Yields:
dict: Data indexed to persist using the indexer storage
"""
for sha1 in self._list_contents_to_index(start, end, indexed):
try:
raw_content = self.objstorage.get(sha1)
except ObjNotFoundError:
self.log.warning('Content %s not found in objstorage' %
hashutil.hash_to_hex(sha1))
continue
res = self.index(sha1, raw_content, **kwargs)
if res:
if not isinstance(res['id'], bytes):
raise TypeError(
'%r.index should return ids as bytes, not %r' %
(self.__class__.__name__, res['id']))
yield res
def _index_with_skipping_already_done(self, start, end):
"""Index not already indexed contents in range [start, end].
Args:
start** (Union[bytes, str]): Starting range identifier
end (Union[bytes, str]): Ending range identifier
Yields:
bytes: Content identifier present in the range
``[start, end]`` which are not already indexed.
"""
while start:
indexed_page = self.indexed_contents_in_range(start, end)
contents = indexed_page['ids']
_end = contents[-1] if contents else end
yield from self._index_contents(
start, _end, contents)
start = indexed_page['next']
def run(self, start, end, skip_existing=True, **kwargs):
"""Given a range of content ids, compute the indexing computations on
the contents within. Either the indexer is incremental
(filter out existing computed data) or not (compute
everything from scratch).
Args:
start (Union[bytes, str]): Starting range identifier
end (Union[bytes, str]): Ending range identifier
skip_existing (bool): Skip existing indexed data
(default) or not
**kwargs: passed to the `index` method
Returns:
bool: True if data was indexed, False otherwise.
"""
with_indexed_data = False
try:
if isinstance(start, str):
start = hashutil.hash_to_bytes(start)
if isinstance(end, str):
end = hashutil.hash_to_bytes(end)
if skip_existing:
gen = self._index_with_skipping_already_done(start, end)
else:
gen = self._index_contents(start, end, indexed=[])
for results in utils.grouper(gen,
n=self.config['write_batch_size']):
self.persist_index_computations(
results, policy_update='update-dups')
with_indexed_data = True
except Exception:
self.log.exception(
'Problem when computing metadata.')
finally:
return with_indexed_data
def origin_get_params(id_):
"""From any of the two types of origin identifiers (int or
type+url), returns a dict that can be passed to Storage.origin_get.
Also accepts JSON-encoded forms of these (used via the task scheduler).
>>> from pprint import pprint
>>> origin_get_params(123)
{'id': 123}
>>> pprint(origin_get_params(['git', 'https://example.com/foo.git']))
{'type': 'git', 'url': 'https://example.com/foo.git'}
>>> origin_get_params("123")
{'id': 123}
>>> pprint(origin_get_params('["git", "https://example.com/foo.git"]'))
{'type': 'git', 'url': 'https://example.com/foo.git'}
"""
if isinstance(id_, str):
# Data coming from JSON, which requires string keys, so
# one extra level of deserialization is needed
id_ = ast.literal_eval(id_)
if isinstance(id_, (tuple, list)):
if len(id_) != 2:
raise TypeError('Expected a (type, url) tuple.')
(type_, url) = id_
params = {'type': type_, 'url': url}
elif isinstance(id_, int):
params = {'id': id_}
else:
raise TypeError('Invalid value in "ids": %r' % id_)
return params
class OriginIndexer(BaseIndexer):
"""An object type indexer, inherits from the :class:`BaseIndexer` and
implements Origin indexing using the run method
Note: the :class:`OriginIndexer` is not an instantiable object.
To use it in another context one should inherit from this class
and override the methods mentioned in the :class:`BaseIndexer`
class.
"""
def run(self, ids, policy_update='update-dups', parse_ids=True,
next_step=None, **kwargs):
"""Given a list of origin ids:
- retrieve origins from storage
- execute the indexing computations
- store the results (according to policy_update)
Args:
ids ([Union[int, Tuple[str, bytes]]]): list of origin ids or
(type, url) tuples.
policy_update (str): either 'update-dups' or 'ignore-dups' to
respectively update duplicates (default) or ignore them
next_step (dict): a dict in the form expected by
`scheduler.backend.SchedulerBackend.create_tasks` without
`next_run`, plus an optional `result_name` key.
parse_ids (bool): Do we need to parse id or not (default)
**kwargs: passed to the `index` method
"""
if parse_ids:
ids = [o.split('+', 1) if ':' in o else int(o) # type+url or id
for o in ids]
origins_filtered = []
origins = self.storage.origin_get(
[origin_get_params(id_) for id_ in ids])
for (id_, origin) in zip(ids, origins):
if not origin:
self.log.warning('Origin %s not found in storage' %
id_)
continue
origins_filtered.append(origin)
results = self.index_list(origins_filtered, **kwargs)
self.persist_index_computations(results, policy_update)
self.results = results
return self.next_step(results, task=next_step)
def index_list(self, origins, **kwargs):
results = []
for origin in origins:
try:
res = self.index(origin, **kwargs)
if res: # If no results, skip it
results.append(res)
except Exception:
self.log.exception(
'Problem when processing origin %s',
origin['id'])
return results
class RevisionIndexer(BaseIndexer):
"""An object type indexer, inherits from the :class:`BaseIndexer` and
implements Revision indexing using the run method
Note: the :class:`RevisionIndexer` is not an instantiable object.
To use it in another context one should inherit from this class
and override the methods mentioned in the :class:`BaseIndexer`
class.
"""
def run(self, ids, policy_update, next_step=None):
"""Given a list of sha1_gits:
- retrieve revisions from storage
- execute the indexing computations
- store the results (according to policy_update)
Args:
ids ([bytes or str]): sha1_git's identifier list
policy_update (str): either 'update-dups' or 'ignore-dups' to
respectively update duplicates or ignore them
"""
results = []
ids = [hashutil.hash_to_bytes(id_) if isinstance(id_, str) else id_
for id_ in ids]
revs = self.storage.revision_get(ids)
for rev in revs:
if not rev:
self.log.warning('Revisions %s not found in storage' %
list(map(hashutil.hash_to_hex, ids)))
continue
try:
res = self.index(rev)
if res: # If no results, skip it
results.append(res)
except Exception:
self.log.exception(
'Problem when processing revision')
self.persist_index_computations(results, policy_update)
self.results = results
return self.next_step(results, task=next_step)

File Metadata

Mime Type
text/x-python
Expires
Fri, Jul 4, 12:44 PM (2 w, 2 d ago)
Storage Engine
blob
Storage Format
Raw Data
Storage Handle
3287181

Event Timeline

About · Developer information · Legal