diff --git a/swh/indexer/indexer.py b/swh/indexer/indexer.py index 72d8b78..234219b 100644 --- a/swh/indexer/indexer.py +++ b/swh/indexer/indexer.py @@ -1,585 +1,585 @@ # 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 os import logging import shutil import tempfile import datetime from copy import deepcopy 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 class DiskIndexer: """Mixin intended to be used with other SomethingIndexer classes. Indexers inheriting from this class are a category of indexers which needs the disk for their computations. Note: This expects `self.working_directory` variable defined at runtime. """ def write_to_temp(self, filename, data): """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(self.working_directory, exist_ok=True) temp_dir = tempfile.mkdtemp(dir=self.working_directory) content_path = os.path.join(temp_dir, filename) with open(content_path, 'wb') as f: f.write(data) return content_path def cleanup(self, content_path): """Remove content_path from working directory. Args: content_path (str): the file to remove """ temp_dir = os.path.dirname(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: :func:`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: :func:`filter`: filter out data already indexed (in storage). :func:`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. :func:`persist_index_computations`: persist the results of multiple index computations in the storage. The new indexer implementation can also override the following functions: :func:`prepare`: Configuration preparation for the indexer. When overriding, this must call the `super().prepare()` instruction. :func:`check`: Configuration check for the indexer. When overriding, this must call the `super().check()` instruction. :func:`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 = {} def __init__(self): """Prepare and check that the indexer is ready to run. """ super().__init__() self.prepare() self.check() def prepare(self): """Prepare the indexer's needed runtime configuration. Without this step, the indexer cannot possibly run. """ self.config = self.parse_config_file( additional_configs=[self.ADDITIONAL_CONFIG]) if self.config['storage']: self.storage = get_storage(**self.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') self.tools = list(self.register_tools(self.config['tools'])) def check(self, *, check_tools=True): """Check the indexer's configuration is ok before proceeding. If ok, does nothing. If not raise error. """ if check_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 of dict with additional id key. Raises: ValueError if not a list nor a dict. """ tools = self.config['tools'] if isinstance(tools, list): - tools = map(self._prepare_tool, tools) + 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) @abc.abstractmethod 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: a dict that makes sense for the persist_index_computations function. """ pass @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 a `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') task['next_run'] = datetime.datetime.now() 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. """ @abc.abstractmethod def filter(self, ids): """Filter missing ids for that particular indexer. Args: ids ([bytes]): list of ids Yields: iterator of missing ids """ pass 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 ([bytes]): 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 a `result_name` key. **kwargs: passed to the `index` method """ 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: Content identifier (bytes) 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: Identifier (bytes) of contents to index. """ while start: result = self.storage.content_get_range(start, end) contents = result['contents'] for c in contents: _id = 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: Data indexed (dict) 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: yield res 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: a boolean. 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: indexed = set(self.indexed_contents_in_range(start, end)) else: indexed = set() index_computations = self._index_contents(start, end, indexed) for results in utils.grouper(index_computations, n=self.config['write_batch_size']): self.persist_index_computations( results, policy_update='update-dups') with_indexed_data = True return with_indexed_data except Exception: self.log.exception( 'Problem when computing metadata.') 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 a `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] results = [] for id_ in ids: 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_) origin = self.storage.origin_get(params) if not origin: self.log.warning('Origins %s not found in storage' % list(ids)) continue try: res = self.index(origin, **kwargs) if origin: # If no results, skip it results.append(res) except Exception: self.log.exception( 'Problem when processing origin %s' % id_) self.persist_index_computations(results, policy_update) self.results = results return self.next_step(results, task=next_step) 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 = [id_.encode() 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)