1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
|
import json
import time
import requests
from confluent_kafka import Consumer, KafkaException
from fatcat_openapi_client import ReleaseEntity, ContainerEntity, ApiClient, ChangelogEntry
from fatcat_tools import *
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",
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 = ReleaseEntity
self.elasticsearch_document_name = "release"
self.transform_func = release_to_elasticsearch
def run(self):
ac = ApiClient()
def fail_fast(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
if p.error:
print("Kafka consumer commit error: {}".format(p.error))
print("Bailing out...")
# 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))
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")
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')
# HACK: work around a bug where container entities got published to
# release_v03 topic
if self.elasticsearch_document_name == "release":
entity_dict = json.loads(json_str)
if entity_dict.get('name') and not entity_dict.get('title'):
continue
entity = entity_from_json(json_str, self.entity_type, api_client=ac)
# TODO: handle deletions from index
bulk_actions.append(json.dumps({
"index": { "_id": entity.ident, },
}))
bulk_actions.append(json.dumps(
self.transform_func(entity)))
print("Upserting, eg, {} (of {} releases in elasticsearch)".format(entity.ident, len(batch)))
elasticsearch_endpoint = "{}/{}/{}/_bulk".format(
self.elasticsearch_backend,
self.elasticsearch_index,
self.elasticsearch_document_name)
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)
print(resp.content)
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,
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,
batch_size=batch_size)
# previous group got corrupted (by pykafka library?)
self.consumer_group = "elasticsearch-updates3"
self.entity_type = ContainerEntity
self.elasticsearch_document_name = "container"
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.elasticsearch_document_name = "changelog"
self.transform_func = changelog_to_elasticsearch
|
