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-rw-r--r--python/fatcat_tools/workers/changelog.py176
-rw-r--r--python/fatcat_tools/workers/elasticsearch.py83
-rw-r--r--python/fatcat_tools/workers/worker_common.py77
3 files changed, 227 insertions, 109 deletions
diff --git a/python/fatcat_tools/workers/changelog.py b/python/fatcat_tools/workers/changelog.py
index 6319d55a..4108012e 100644
--- a/python/fatcat_tools/workers/changelog.py
+++ b/python/fatcat_tools/workers/changelog.py
@@ -1,7 +1,7 @@
import json
import time
-from pykafka.common import OffsetType
+from confluent_kafka import Consumer, Producer, KafkaException
from .worker_common import FatcatWorker, most_recent_message
@@ -12,7 +12,7 @@ class ChangelogWorker(FatcatWorker):
found, fetch them and push (as JSON) into a Kafka topic.
"""
- def __init__(self, api, kafka_hosts, produce_topic, poll_interval=10.0, offset=None):
+ def __init__(self, api, kafka_hosts, produce_topic, poll_interval=5.0, offset=None):
# TODO: should be offset=0
super().__init__(kafka_hosts=kafka_hosts,
produce_topic=produce_topic,
@@ -21,38 +21,47 @@ class ChangelogWorker(FatcatWorker):
self.offset = offset # the fatcat changelog offset, not the kafka offset
def run(self):
- topic = self.kafka.topics[self.produce_topic]
+
# On start, try to consume the most recent from the topic, and using
# that as the starting offset. Note that this is a single-partition
# topic
if self.offset is None:
print("Checking for most recent changelog offset...")
- msg = most_recent_message(topic)
+ msg = most_recent_message(self.produce_topic, self.kafka_config)
if msg:
self.offset = json.loads(msg.decode('utf-8'))['index']
else:
- self.offset = 1
-
- with topic.get_producer(
- max_request_size=self.produce_max_request_size,
- ) as producer:
- while True:
- latest = int(self.api.get_changelog(limit=1)[0].index)
- if latest > self.offset:
- print("Fetching changelogs from {} through {}".format(
- self.offset+1, latest))
- for i in range(self.offset+1, latest+1):
- cle = self.api.get_changelog_entry(i)
- obj = self.api.api_client.sanitize_for_serialization(cle)
- producer.produce(
- message=json.dumps(obj).encode('utf-8'),
- partition_key=None,
- timestamp=None,
- #NOTE could be (???): timestamp=cle.timestamp,
- )
- self.offset = i
- print("Sleeping {} seconds...".format(self.poll_interval))
- time.sleep(self.poll_interval)
+ self.offset = 0
+ print("Most recent changelog index in Kafka seems to be {}".format(self.offset))
+
+ def fail_fast(err, msg):
+ if err is not None:
+ print("Kafka producer delivery error: {}".format(err))
+ print("Bailing out...")
+ # TODO: should it be sys.exit(-1)?
+ raise KafkaException(err)
+
+ producer = Producer(self.kafka_config)
+
+ while True:
+ latest = int(self.api.get_changelog(limit=1)[0].index)
+ if latest > self.offset:
+ print("Fetching changelogs from {} through {}".format(
+ self.offset+1, latest))
+ for i in range(self.offset+1, latest+1):
+ cle = self.api.get_changelog_entry(i)
+ obj = self.api.api_client.sanitize_for_serialization(cle)
+ producer.produce(
+ self.produce_topic,
+ json.dumps(obj).encode('utf-8'),
+ key=str(i),
+ on_delivery=fail_fast,
+ #NOTE timestamp could be timestamp=cle.timestamp (?)
+ )
+ self.offset = i
+ producer.poll(0)
+ print("Sleeping {} seconds...".format(self.poll_interval))
+ time.sleep(self.poll_interval)
class EntityUpdatesWorker(FatcatWorker):
@@ -63,45 +72,94 @@ class EntityUpdatesWorker(FatcatWorker):
For now, only release updates are published.
"""
- def __init__(self, api, kafka_hosts, consume_topic, release_topic):
+ def __init__(self, api, kafka_hosts, consume_topic, release_topic, poll_interval=5.0):
super().__init__(kafka_hosts=kafka_hosts,
consume_topic=consume_topic,
api=api)
self.release_topic = release_topic
+ self.poll_interval = poll_interval
self.consumer_group = "entity-updates"
def run(self):
- changelog_topic = self.kafka.topics[self.consume_topic]
- release_topic = self.kafka.topics[self.release_topic]
-
- consumer = changelog_topic.get_balanced_consumer(
- consumer_group=self.consumer_group,
- managed=True,
- auto_offset_reset=OffsetType.LATEST,
- reset_offset_on_start=False,
- fetch_message_max_bytes=4000000, # up to ~4MBytes
- auto_commit_enable=True,
- auto_commit_interval_ms=30000, # 30 seconds
- compacted_topic=True,
+
+ def fail_fast(err, msg):
+ if err is not None:
+ print("Kafka producer delivery error: {}".format(err))
+ print("Bailing out...")
+ # TODO: should it be sys.exit(-1)?
+ raise KafkaException(err)
+
+ def on_commit(err, partitions):
+ if err is not None:
+ print("Kafka consumer commit error: {}".format(err))
+ print("Bailing out...")
+ # TODO: should it be sys.exit(-1)?
+ raise KafkaException(err)
+ for p in partitions:
+ # check for partition-specific commit errors
+ print(p)
+ if p.error:
+ print("Kafka consumer commit error: {}".format(p.error))
+ print("Bailing out...")
+ # TODO: should it be sys.exit(-1)?
+ raise KafkaException(err)
+ 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))
+
+ consumer_conf = self.kafka_config.copy()
+ consumer_conf.update({
+ 'group.id': self.consumer_group,
+ 'enable.auto.offset.store': False,
+ 'default.topic.config': {
+ 'auto.offset.reset': 'latest',
+ },
+ })
+ consumer = Consumer(consumer_conf)
+
+ producer_conf = self.kafka_config.copy()
+ producer_conf.update({
+ 'default.topic.config': {
+ 'request.required.acks': -1,
+ },
+ })
+ producer = Producer(producer_conf)
+
+ consumer.subscribe([self.consume_topic],
+ on_assign=on_rebalance,
+ on_revoke=on_rebalance,
)
+ print("Kafka consuming {}".format(self.consume_topic))
+
+ while True:
+ msg = consumer.poll(self.poll_interval)
+ if not msg:
+ print("nothing new from kafka (interval:{})".format(self.poll_interval))
+ consumer.commit()
+ continue
+ if msg.error():
+ raise KafkaException(msg.error())
+
+ cle = json.loads(msg.value().decode('utf-8'))
+ #print(cle)
+ print("processing changelog index {}".format(cle['index']))
+ release_edits = cle['editgroup']['edits']['releases']
+ for re in release_edits:
+ ident = re['ident']
+ release = self.api.get_release(ident, expand="files,filesets,webcaptures,container")
+ # TODO: use .to_json() helper
+ release_dict = self.api.api_client.sanitize_for_serialization(release)
+ producer.produce(
+ self.release_topic,
+ json.dumps(release_dict).encode('utf-8'),
+ key=ident.encode('utf-8'),
+ on_delivery=fail_fast,
+ )
+ consumer.store_offsets(msg)
- # using a sync producer to try and avoid racey loss of delivery (aka,
- # if consumer group updated but produce didn't stick)
- with release_topic.get_sync_producer(
- max_request_size=self.produce_max_request_size,
- ) as producer:
- for msg in consumer:
- cle = json.loads(msg.value.decode('utf-8'))
- #print(cle)
- print("processing changelog index {}".format(cle['index']))
- release_edits = cle['editgroup']['edits']['releases']
- for re in release_edits:
- ident = re['ident']
- release = self.api.get_release(ident, expand="files,filesets,webcaptures,container")
- release_dict = self.api.api_client.sanitize_for_serialization(release)
- producer.produce(
- message=json.dumps(release_dict).encode('utf-8'),
- partition_key=ident.encode('utf-8'),
- timestamp=None,
- )
- #consumer.commit_offsets()
diff --git a/python/fatcat_tools/workers/elasticsearch.py b/python/fatcat_tools/workers/elasticsearch.py
index 83310284..bb7f0cfb 100644
--- a/python/fatcat_tools/workers/elasticsearch.py
+++ b/python/fatcat_tools/workers/elasticsearch.py
@@ -2,7 +2,7 @@
import json
import time
import requests
-from pykafka.common import OffsetType
+from confluent_kafka import Consumer, Producer, KafkaException
from fatcat_client import ReleaseEntity, ApiClient
from fatcat_tools import *
@@ -17,36 +17,77 @@ class ElasticsearchReleaseWorker(FatcatWorker):
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"):
+ def __init__(self, kafka_hosts, consume_topic, poll_interval=5.0, offset=None,
+ elasticsearch_backend="http://localhost:9200", elasticsearch_index="fatcat",
+ batch_size=200):
super().__init__(kafka_hosts=kafka_hosts,
consume_topic=consume_topic)
self.consumer_group = "elasticsearch-updates"
+ self.batch_size = batch_size
+ self.poll_interval = poll_interval
self.elasticsearch_backend = elasticsearch_backend
self.elasticsearch_index = elasticsearch_index
def run(self):
- consume_topic = self.kafka.topics[self.consume_topic]
ac = ApiClient()
- consumer = consume_topic.get_balanced_consumer(
- consumer_group=self.consumer_group,
- managed=True,
- fetch_message_max_bytes=4000000, # up to ~4MBytes
- auto_commit_enable=True,
- auto_commit_interval_ms=30000, # 30 seconds
- compacted_topic=True,
+ def on_rebalance(consumer, partitions):
+ for p in partitions:
+ if p.error:
+ raise KafkaException(p.error)
+ print("Kafka partitions rebalanced: {} / {}".format(
+ consumer, partitions))
+
+ consumer_conf = self.kafka_config.copy()
+ consumer_conf.update({
+ 'group.id': self.consumer_group,
+ 'enable.auto.offset.store': False,
+ 'default.topic.config': {
+ 'auto.offset.reset': 'latest',
+ },
+ })
+ consumer = Consumer(consumer_conf)
+ consumer.subscribe([self.consume_topic],
+ on_assign=on_rebalance,
+ on_revoke=on_rebalance,
)
- for msg in consumer:
- json_str = msg.value.decode('utf-8')
- release = entity_from_json(json_str, ReleaseEntity, api_client=ac)
- #print(release)
- elasticsearch_endpoint = "{}/{}/release/{}".format(
+ 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")
+ print("... nothing new from kafka, try again (interval: {}".format(self.poll_interval))
+ continue
+ print("... got {} kafka messages".format(len(batch)))
+ # 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, ReleaseEntity, api_client=ac)
+ print("Upserting: release/{}".format(entity.ident))
+ bulk_actions.append(json.dumps({
+ "index": { "_id": entity.ident, },
+ }))
+ bulk_actions.append(json.dumps(
+ release_to_elasticsearch(entity)))
+ elasticsearch_endpoint = "{}/{}/release/_bulk".format(
self.elasticsearch_backend,
- self.elasticsearch_index,
- release.ident)
- print("Updating document: {}".format(elasticsearch_endpoint))
- resp = requests.post(elasticsearch_endpoint, json=release_to_elasticsearch(release))
+ self.elasticsearch_index)
+ resp = requests.post(elasticsearch_endpoint,
+ headers={"Content-Type": "application/x-ndjson"},
+ data="\n".join(bulk_actions) + "\n")
resp.raise_for_status()
- #consumer.commit_offsets()
+ if resp.json()['errors']:
+ desc = "Elasticsearch errors from post to {}:".format(elasticsearch_endpoint)
+ print(desc)
+ print(resp.content)
+ raise Exception(desc)
+ consumer.store_offsets(batch[-1])
+
diff --git a/python/fatcat_tools/workers/worker_common.py b/python/fatcat_tools/workers/worker_common.py
index cb4e5dab..1d465f58 100644
--- a/python/fatcat_tools/workers/worker_common.py
+++ b/python/fatcat_tools/workers/worker_common.py
@@ -5,41 +5,56 @@ import csv
import json
import itertools
from itertools import islice
-from pykafka import KafkaClient
-from pykafka.common import OffsetType
+from confluent_kafka import Consumer, KafkaException, TopicPartition
import fatcat_client
from fatcat_client.rest import ApiException
-def most_recent_message(topic):
+def most_recent_message(topic, kafka_config):
"""
Tries to fetch the most recent message from a given topic.
- This only makes sense for single partition topics, though could be
- extended with "last N" behavior.
- Following "Consuming the last N messages from a topic"
- from https://pykafka.readthedocs.io/en/latest/usage.html#consumer-patterns
+ This only makes sense for single partition topics (it works with only the
+ first partition), though could be extended with "last N" behavior.
"""
- consumer = topic.get_simple_consumer(
- auto_offset_reset=OffsetType.LATEST,
- reset_offset_on_start=True)
- offsets = [(p, op.last_offset_consumed - 1)
- for p, op in consumer._partitions.items()]
- offsets = [(p, (o if o > -1 else -2)) for p, o in offsets]
- if -2 in [o for p, o in offsets]:
- consumer.stop()
+
+ print("Fetching most Kafka message from {}".format(topic))
+
+ conf = kafka_config.copy()
+ conf.update({
+ 'group.id': 'worker-init-last-msg', # should never commit
+ 'delivery.report.only.error': True,
+ 'enable.auto.commit': False,
+ 'default.topic.config': {
+ 'request.required.acks': -1,
+ 'auto.offset.reset': 'latest',
+ },
+ })
+
+ consumer = Consumer(conf)
+
+ hwm = consumer.get_watermark_offsets(
+ TopicPartition(topic, 0),
+ timeout=5.0,
+ cached=False)
+ if not hwm:
+ raise Exception("Kafka consumer timeout, or topic {} doesn't exist".format(topic))
+ print("High watermarks: {}".format(hwm))
+
+ if hwm[1] == 0:
+ print("topic is new; not 'most recent message'")
return None
- else:
- consumer.reset_offsets(offsets)
- msg = islice(consumer, 1)
- if msg:
- val = list(msg)[0].value
- consumer.stop()
- return val
- else:
- consumer.stop()
- return None
+
+ consumer.assign([TopicPartition(topic, 0, hwm[1]-1)])
+ msg = consumer.poll(2.0)
+ consumer.close()
+ if not msg:
+ raise Exception("Failed to fetch most recent kafka message")
+ if msg.error():
+ raise KafkaException(msg.error())
+ return msg.value()
+
class FatcatWorker:
"""
@@ -49,9 +64,13 @@ class FatcatWorker:
def __init__(self, kafka_hosts, produce_topic=None, consume_topic=None, api=None):
if api:
self.api = api
- self.kafka = KafkaClient(hosts=kafka_hosts, broker_version="1.0.0")
+ self.kafka_config = {
+ 'bootstrap.servers': kafka_hosts,
+ 'delivery.report.only.error': True,
+ 'message.max.bytes': 20000000, # ~20 MBytes; broker is ~50 MBytes
+ 'default.topic.config': {
+ 'request.required.acks': 'all',
+ },
+ }
self.produce_topic = produce_topic
self.consume_topic = consume_topic
-
- # Kafka producer batch size tuning; also limit on size of single document
- self.produce_max_request_size = 10000000 # 10 MByte-ish