import json import sys import elasticsearch import requests from confluent_kafka import Consumer, KafkaException from fatcat_openapi_client import ApiClient, ChangelogEntry, ContainerEntity, ReleaseEntity from fatcat_tools import entity_from_json, public_api from fatcat_tools.transforms import ( changelog_to_elasticsearch, container_to_elasticsearch, release_to_elasticsearch, ) from fatcat_web.search import get_elastic_container_stats from .worker_common import FatcatWorker class ElasticsearchReleaseWorker(FatcatWorker): """ Consumes from release-updates topic and pushes into (presumably local) elasticsearch. Uses a consumer group to manage offset. """ def __init__( self, kafka_hosts, consume_topic, poll_interval=10.0, offset=None, elasticsearch_backend="http://localhost:9200", elasticsearch_index="fatcat", elasticsearch_release_index="fatcat_releases", batch_size=200, api_host="https://api.fatcat.wiki/v0", query_stats=False, ): super().__init__(kafka_hosts=kafka_hosts, consume_topic=consume_topic) self.consumer_group = "elasticsearch-updates3" self.batch_size = batch_size self.poll_interval = poll_interval self.elasticsearch_backend = elasticsearch_backend self.elasticsearch_index = elasticsearch_index self.elasticsearch_release_index = elasticsearch_release_index self.entity_type = ReleaseEntity self.transform_func = release_to_elasticsearch self.api_host = api_host self.query_stats = query_stats def run(self): ac = ApiClient() api = public_api(self.api_host) # only used by container indexing query_stats code path es_client = elasticsearch.Elasticsearch(self.elasticsearch_backend) def fail_fast(err, partitions): if err is not None: print("Kafka consumer commit error: {}".format(err), file=sys.stderr) print("Bailing out...", file=sys.stderr) # TODO: should it be sys.exit(-1)? raise KafkaException(err) for p in partitions: # check for partition-specific commit errors if p.error: print("Kafka consumer commit error: {}".format(p.error), file=sys.stderr) print("Bailing out...", file=sys.stderr) # TODO: should it be sys.exit(-1)? raise KafkaException(p.error) # print("Kafka consumer commit successful") pass def on_rebalance(consumer, partitions): for p in partitions: if p.error: raise KafkaException(p.error) print( "Kafka partitions rebalanced: {} / {}".format(consumer, partitions), file=sys.stderr, ) consumer_conf = self.kafka_config.copy() consumer_conf.update( { "group.id": self.consumer_group, "on_commit": fail_fast, # messages don't have offset marked as stored until pushed to # elastic, but we do auto-commit stored offsets to broker "enable.auto.commit": True, "enable.auto.offset.store": False, # user code timeout; if no poll after this long, assume user code # hung and rebalance (default: 5min) "max.poll.interval.ms": 60000, "default.topic.config": { "auto.offset.reset": "latest", }, } ) consumer = Consumer(consumer_conf) consumer.subscribe( [self.consume_topic], on_assign=on_rebalance, on_revoke=on_rebalance, ) while True: batch = consumer.consume(num_messages=self.batch_size, timeout=self.poll_interval) if not batch: if not consumer.assignment(): print("... no Kafka consumer partitions assigned yet", file=sys.stderr) print( "... nothing new from kafka, try again (interval: {}".format( self.poll_interval ), file=sys.stderr, ) continue print("... got {} kafka messages".format(len(batch)), file=sys.stderr) # first check errors on entire batch... for msg in batch: if msg.error(): raise KafkaException(msg.error()) # ... then process bulk_actions = [] for msg in batch: json_str = msg.value().decode("utf-8") entity = entity_from_json(json_str, self.entity_type, api_client=ac) assert isinstance(entity, self.entity_type) if self.entity_type == ChangelogEntry: key = entity.index # might need to fetch from API if not ( entity.editgroup and entity.editgroup.editor ): # pylint: disable=no-member # (TODO) entity = api.get_changelog_entry(entity.index) else: key = entity.ident # pylint: disable=no-member # (TODO) if self.entity_type != ChangelogEntry and entity.state == "wip": print( f"WARNING: skipping state=wip entity: {self.entity_type.__name__} {entity.ident}", file=sys.stderr, ) continue if self.entity_type == ContainerEntity and self.query_stats: stats = get_elastic_container_stats( entity.ident, es_client=es_client, es_index=self.elasticsearch_release_index, merge_shadows=True, ) doc_dict = container_to_elasticsearch(entity, stats=stats) else: doc_dict = self.transform_func(entity) # TODO: handle deletions from index bulk_actions.append( json.dumps( { "index": { "_id": key, }, } ) ) bulk_actions.append(json.dumps(doc_dict)) # if only WIP entities, then skip if not bulk_actions: for msg in batch: consumer.store_offsets(message=msg) continue print( "Upserting, eg, {} (of {} {} in elasticsearch)".format( key, len(batch), self.entity_type.__name__ ), file=sys.stderr, ) elasticsearch_endpoint = "{}/{}/_bulk".format( self.elasticsearch_backend, self.elasticsearch_index ) resp = requests.post( elasticsearch_endpoint, headers={"Content-Type": "application/x-ndjson"}, data="\n".join(bulk_actions) + "\n", ) resp.raise_for_status() if resp.json()["errors"]: desc = "Elasticsearch errors from post to {}:".format(elasticsearch_endpoint) print(desc, file=sys.stderr) print(resp.content, file=sys.stderr) raise Exception(desc) for msg in batch: # offsets are *committed* (to brokers) automatically, but need # to be marked as processed here consumer.store_offsets(message=msg) class ElasticsearchContainerWorker(ElasticsearchReleaseWorker): def __init__( self, kafka_hosts, consume_topic, poll_interval=10.0, offset=None, query_stats=False, elasticsearch_release_index="fatcat_release", elasticsearch_backend="http://localhost:9200", elasticsearch_index="fatcat", batch_size=200, ): super().__init__( kafka_hosts=kafka_hosts, consume_topic=consume_topic, poll_interval=poll_interval, offset=offset, elasticsearch_backend=elasticsearch_backend, elasticsearch_index=elasticsearch_index, elasticsearch_release_index=elasticsearch_release_index, query_stats=query_stats, batch_size=batch_size, ) # previous group got corrupted (by pykafka library?) self.consumer_group = "elasticsearch-updates3" self.entity_type = ContainerEntity self.transform_func = container_to_elasticsearch class ElasticsearchChangelogWorker(ElasticsearchReleaseWorker): """ Pulls changelog messages from Kafka, runs transformations and indexes them. Note: Very early versions of changelog entries did not contain details about the editor or extra fields. """ def __init__( self, kafka_hosts, consume_topic, poll_interval=10.0, offset=None, elasticsearch_backend="http://localhost:9200", elasticsearch_index="fatcat_changelog", batch_size=200, ): super().__init__(kafka_hosts=kafka_hosts, consume_topic=consume_topic) self.consumer_group = "elasticsearch-updates3" self.batch_size = batch_size self.poll_interval = poll_interval self.elasticsearch_backend = elasticsearch_backend self.elasticsearch_index = elasticsearch_index self.entity_type = ChangelogEntry self.transform_func = changelog_to_elasticsearch