diff --git a/swh/scheduler/backend_es.py b/swh/scheduler/backend_es.py index a7ebf64..82cb02f 100644 --- a/swh/scheduler/backend_es.py +++ b/swh/scheduler/backend_es.py @@ -1,247 +1,266 @@ # Copyright (C) 2018-2019 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 """Elastic Search backend """ +import datetime # noqa import logging from copy import deepcopy +from typing import Any, Dict -from swh.core import utils -from elasticsearch import Elasticsearch from elasticsearch import helpers +from swh.core import utils + logger = logging.getLogger(__name__) DEFAULT_CONFIG = { - 'elastic_search': { - 'storage_nodes': {'host': 'localhost', 'port': 9200}, - 'index_name_prefix': 'swh-tasks', - 'client_options': { - 'sniff_on_start': False, - 'sniff_on_connection_fail': True, - 'http_compress': False, + 'elasticsearch': { + 'cls': 'local', + 'args': { + 'index_name_prefix': 'swh-tasks', + 'storage_nodes': ['localhost:9200'], + 'client_options': { + 'sniff_on_start': False, + 'sniff_on_connection_fail': True, + 'http_compress': False, + 'sniffer_timeout': 60 + }, }, - }, + } } +def get_elasticsearch(cls: str, args: Dict[str, Any] = {}): + """Instantiate an elastic search instance + + """ + if cls == 'local': + from elasticsearch import Elasticsearch + else: + raise ValueError('Unknown elasticsearch class `%s`' % cls) + + return Elasticsearch(**args) + + class ElasticSearchBackend: """ElasticSearch backend to index tasks + This uses an elasticsearch client to actually discuss with the + elasticsearch instance. + """ def __init__(self, **config): self.config = deepcopy(DEFAULT_CONFIG) self.config.update(config) - es_conf = self.config['elastic_search'] - options = es_conf.get('client_options', {}) - self.storage = Elasticsearch( - # nodes to use by default - es_conf['storage_nodes'], - # auto detect cluster's status - sniff_on_start=options['sniff_on_start'], - sniff_on_connection_fail=options['sniff_on_connection_fail'], - sniffer_timeout=60, - # compression or not - http_compress=options['http_compress']) - self.index_name_prefix = es_conf['index_name_prefix'] + es_conf = self.config['elasticsearch'] + args = deepcopy(es_conf['args']) + self.index_name_prefix = args.pop('index_name_prefix') + self.storage = get_elasticsearch( + cls=es_conf['cls'], + args={ + 'storage_nodes': args.get('storage_nodes', []), + **args.get('client_options', {}), + } + ) # document's index type (cf. /data/elastic-template.json) self.doc_type = 'task' def initialize(self): self.storage.indices.put_mapping( index=f"{self.index_name_prefix}-*", doc_type=self.doc_type, # to allow type definition below include_type_name=True, # to allow install mapping even if no index yet allow_no_indices=True, body={ "properties": { "task_id": {"type": "double"}, "task_policy": {"type": "text"}, "task_status": {"type": "text"}, "task_run_id": {"type": "double"}, "arguments": { "type": "object", "properties": { "args": { "type": "nested", "dynamic": False }, "kwargs": { "type": "text" } } }, "type": {"type": "text"}, "backend_id": {"type": "text"}, "metadata": { "type": "object", "enabled": False }, "scheduled": { "type": "date", "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||strict_date_optional_time||epoch_millis" # noqa }, "started": { "type": "date", "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||strict_date_optional_time||epoch_millis" # noqa }, "ended": { "type": "date", "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||strict_date_optional_time||epoch_millis" # noqa } } }) self.storage.indices.put_settings( index=f"{self.index_name_prefix}-*", allow_no_indices=True, body={ "index": { "codec": "best_compression", "refresh_interval": "1s", "number_of_shards": 1 } }) def create(self, index_name) -> None: """Create and initialize index_name with mapping for all indices matching `swh-tasks-` pattern """ assert index_name.startswith(self.index_name_prefix) self.storage.indices.create(index_name) def compute_index_name(self, year, month): """Given a year, month, compute the index's name. """ return '%s-%s-%s' % ( self.index_name_prefix, year, '%02d' % month) def mget(self, index_name, doc_ids, chunk_size=500, source=True): """Retrieve document's full content according to their ids as per source's setup. The `source` allows to retrieve only what's interesting, e.g: - source=True ; gives back the original indexed data - source=False ; returns without the original _source field - source=['task_id'] ; returns only task_id in the _source field Args: index_name (str): Name of the concerned index. doc_ids (generator): Generator of ids to retrieve chunk_size (int): Number of documents chunk to send for retrieval source (bool/[str]): Source of information to return Yields: document indexed as per source's setup """ if isinstance(source, list): source = {'_source': ','.join(source)} else: source = {'_source': str(source).lower()} for ids in utils.grouper(doc_ids, n=1000): res = self.storage.mget(body={'ids': list(ids)}, index=index_name, doc_type=self.doc_type, params=source) if not res: logger.error('Error during retrieval of data, skipping!') continue for doc in res['docs']: found = doc.get('found') if not found: msg = 'Doc id %s not found, not indexed yet' % doc['_id'] logger.warning(msg) continue yield doc['_source'] def _streaming_bulk(self, index_name, doc_stream, chunk_size=500): """Bulk index data and returns the successful indexed data's identifier. Args: index_name (str): Name of the concerned index. doc_stream (generator): Generator of documents to index chunk_size (int): Number of documents chunk to send for indexation Yields: document id indexed """ actions = ({'_index': index_name, '_op_type': 'index', '_type': self.doc_type, '_source': data} for data in doc_stream) for ok, result in helpers.streaming_bulk(client=self.storage, actions=actions, chunk_size=chunk_size, raise_on_error=False, raise_on_exception=False): if not ok: logger.error('Error during %s indexation. Skipping.', result) continue yield result['index']['_id'] def is_index_opened(self, index_name: str) -> bool: """Determine if an index is opened or not """ try: self.storage.indices.stats(index_name) return True except Exception: # fails when indice is closed (no other api call found) return False def streaming_bulk(self, index_name, doc_stream, chunk_size=500, source=True): """Bulk index data and returns the successful indexed data as per source's setup. the `source` permits to retrieve only what's of interest to us, e.g: - source=True ; gives back the original indexed data - source=False ; returns without the original _source field - source=['task_id'] ; returns only task_id in the _source field Args: index_name (str): Name of the concerned index. doc_stream (generator): Document generator to index chunk_size (int): Number of documents chunk to send source (bool, [str]): the information to return """ to_close = False # index must exist if not self.storage.indices.exists(index_name): self.create(index_name) # Close that new index (to avoid too much opened indices) to_close = True # index must be opened if not self.is_index_opened(index_name): to_close = True self.storage.indices.open(index_name) try: indexed_ids = self._streaming_bulk( index_name, doc_stream, chunk_size=chunk_size) yield from self.mget( index_name, indexed_ids, chunk_size=chunk_size, source=source) finally: # closing it to stay in the same state as prior to the call if to_close: self.storage.indices.close(index_name)