我正在用Kafka建立一个数据管道。数据流程如下:在mongodb中捕获数据更改并将其发送到ElasticSearch。
MongoDB
由于我还在测试,Kafka相关的系统都是在单台服务器上运行的。
>
启动zookeepr
$ bin/zookeeper-server-start etc/kafka/zookeeper.properties
启动引导服务器
$ bin/kafka-server-start etc/kafka/server.properties
$ bin/schema-registry-start etc/schema-registry/schema-registry.properties
$ bin/connect-standalone \
etc/schema-registry/connect-avro-standalone.properties \
etc/kafka/connect-mongo-source.properties
$ cat etc/kafka/connect-mongo-source.properties
>>>
name=mongodb-source-connector
connector.class=io.debezium.connector.mongodb.MongoDbConnector
mongodb.hosts=''
initial.sync.max.threads=1
tasks.max=1
mongodb.name=higee
$ cat etc/schema-registry/connect-avro-standalone.properties
>>>
bootstrap.servers=localhost:9092
key.converter=io.confluent.connect.avro.AvroConverter
key.converter.schema.registry.url=http://localhost:8081
value.converter=io.confluent.connect.avro.AvroConverter
value.converter.schema.registry.url=http://localhost:8081
internal.key.converter=org.apache.kafka.connect.json.JsonConverter
internal.value.converter=org.apache.kafka.connect.json.JsonConverter
internal.key.converter.schemas.enable=false
internal.value.converter.schemas.enable=false
rest.port=8083
$ bin/connect-standalone \
etc/schema-registry/connect-avro-standalone2.properties \
etc/kafka-connect-elasticsearch/elasticsearch.properties
$ cat etc/kafka-connect-elasticsearch/elasticsearch.properties
>>>
name=elasticsearch-sink
connector.class=io.confluent.connect.elasticsearch.ElasticsearchSinkConnector
tasks.max=1
topics=higee.higee.higee
key.ignore=true
connection.url=''
type.name=kafka-connect
$ cat etc/schema-registry/connect-avro-standalone2.properties
>>>
bootstrap.servers=localhost:9092
key.converter=io.confluent.connect.avro.AvroConverter
key.converter.schema.registry.url=http://localhost:8081
value.converter=io.confluent.connect.avro.AvroConverter
value.converter.schema.registry.url=http://localhost:8081
internal.key.converter=org.apache.kafka.connect.json.JsonConverter
internal.value.converter=org.apache.kafka.connect.json.\
JsonConverter
internal.key.converter.schemas.enable=false
internal.value.converter.schemas.enable=false
rest.port=8084
$ bin/kafka-avro-console-consumer \
--bootstrap-server localhost:9092 \
--topic higee.higee.higee --from-beginning | jq
然后,我得到以下结果。
"after": null,
"patch": {
"string": "{\"_id\" : {\"$oid\" : \"5ad97f982a0f383bb638ecac\"},\"name\" : \"higee\",\"salary\" : 100,\"origin\" : \"South Korea\"}"
},
"source": {
"version": {
"string": "0.7.5"
},
"name": "higee",
"rs": "172.31.50.13",
"ns": "higee",
"sec": 1524214412,
"ord": 1,
"h": {
"long": -2379508538412995600
},
"initsync": {
"boolean": false
}
},
"op": {
"string": "u"
},
"ts_ms": {
"long": 1524214412159
}
}
然后,如果我去elasticsearch,我会得到以下结果。
{
"_index": "higee.higee.higee",
"_type": "kafka-connect",
"_id": "higee.higee.higee+0+3",
"_score": 1,
"_source": {
"after": null,
"patch": """{"_id" : {"$oid" : "5ad97f982a0f383bb638ecac"},
"name" : "higee",
"salary" : 100,
"origin" : "South Korea"}""",
"source": {
"version": "0.7.5",
"name": "higee",
"rs": "172.31.50.13",
"ns": "higee",
"sec": 1524214412,
"ord": 1,
"h": -2379508538412995600,
"initsync": false
},
"op": "u",
"ts_ms": 1524214412159
}
}
我想实现的一个目标是
{
"_index": "higee.higee.higee",
"_type": "kafka-connect",
"_id": "higee.higee.higee+0+3",
"_score": 1,
"_source": {
"oid" : "5ad97f982a0f383bb638ecac",
"name" : "higee",
"salary" : 100,
"origin" : "South Korea"
}"
}
input {
kafka {
bootstrap_servers => ["localhost:9092"]
topics => ["higee.higee.higee"]
auto_offset_reset => "earliest"
codec => json {
charset => "UTF-8"
}
}
}
filter {
json {
source => "message"
}
}
output {
stdout {
codec => rubydebug
}
}
{
"message" => "H\u0002�\u0001{\"_id\" : \
{\"$oid\" : \"5adafc0e2a0f383bb63910a6\"}, \
\"name\" : \"higee\", \
\"salary\" : 101, \
\"origin\" : \"South Korea\"} \
\u0002\n0.7.5\nhigee \
\u0018172.31.50.13\u001Ahigee.higee2 \
��ح\v\u0002\u0002��̗���� \u0002\u0002u\u0002�����X",
"tags" => [[0] "_jsonparsefailure"]
}
案例2
>
logstash.conf
input {
kafka {
bootstrap_servers => ["localhost:9092"]
topics => ["higee.higee.higee"]
auto_offset_reset => "earliest"
codec => avro {
schema_uri => "./test.avsc"
}
}
}
filter {
json {
source => "message"
}
}
output {
stdout {
codec => rubydebug
}
}
test.avsc
{
"namespace": "example",
"type": "record",
"name": "Higee",
"fields": [
{"name": "_id", "type": "string"},
{"name": "name", "type": "string"},
{"name": "salary", "type": "int"},
{"name": "origin", "type": "string"}
]
}
An unexpected error occurred! {:error=>#<NoMethodError:
undefined method `type_sym' for nil:NilClass>, :backtrace=>
["/home/ec2-user/logstash-
6.1.0/vendor/bundle/jruby/2.3.0/gems/avro-
1.8.2/lib/avro/io.rb:224:in `match_schemas'", "/home/ec2-
user/logstash-6.1.0/vendor/bundle/jruby/2.3.0/gems/avro-
1.8.2/lib/avro/io.rb:280:in `read_data'", "/home/ec2-
user/logstash-6.1.0/vendor/bundle/jruby/2.3.0/gems/avro-
1.8.2/lib/avro/io.rb:376:in `read_union'", "/home/ec2-
user/logstash-6.1.0/vendor/bundle/jruby/2.3.0/gems/avro-
1.8.2/lib/avro/io.rb:309:in `read_data'", "/home/ec2-
user/logstash-6.1.0/vendor/bundle/jruby/2.3.0/gems/avro-
1.8.2/lib/avro/io.rb:384:in `block in read_record'",
"org/jruby/RubyArray.java:1734:in `each'", "/home/ec2-
user/logstash-6.1.0/vendor/bundle/jruby/2.3.0/gems/avro-
1.8.2/lib/avro/io.rb:382:in `read_record'", "/home/ec2-
user/logstash-6.1.0/vendor/bundle/jruby/2.3.0/gems/avro-
1.8.2/lib/avro/io.rb:310:in `read_data'", "/home/ec2-
user/logstash-6.1.0/vendor/bundle/jruby/2.3.0/gems/avro-
1.8.2/lib/avro/io.rb:275:in `read'", "/home/ec2-
user/logstash-6.1.0/vendor/bundle/jruby/2.3.0/gems/
logstash-codec-avro-3.2.3-java/lib/logstash/codecs/
avro.rb:77:in `decode'", "/home/ec2-user/logstash-6.1.0/
vendor/bundle/jruby/2.3.0/gems/logstash-input-kafka-
8.0.2/lib/ logstash/inputs/kafka.rb:254:in `block in
thread_runner'", "/home/ec2-user/logstash-
6.1.0/vendor/bundle/jruby/2.3.0/gems/logstash-input-kafka-
8.0.2/lib/logstash/inputs/kafka.rb:253:in `block in
thread_runner'"]}
python客户端
>
Kafka
库:无法解码消息
from kafka import KafkaConsumer
consumer = KafkaConsumer(
topics='higee.higee.higee',
auto_offset_reset='earliest'
)
for message in consumer:
message.value.decode('utf-8')
>>> 'utf-8' codec can't decode byte 0xe4 in position 6:
invalid continuation byte
confluent_kafka
与python 3不兼容
提前道谢。
一些尝试
$ cat etc/kafka/connect-mongo-source.properties
>>>
name=mongodb-source-connector
connector.class=io.debezium.connector.mongodb.MongoDbConnector
mongodb.hosts=''
initial.sync.max.threads=1
tasks.max=1
mongodb.name=higee
transforms=unwrap
transforms.unwrap.type = io.debezium.connector.mongodbtransforms.UnwrapFromMongoDbEnvelope
ERROR WorkerSourceTask{id=mongodb-source-connector-0} Task threw an uncaught and unrecoverable exception (org.apache.kafka.connect.runtime.WorkerTask:172)
org.bson.json.JsonParseException: JSON reader expected a string but found '0'.
at org.bson.json.JsonReader.visitBinDataExtendedJson(JsonReader.java:904)
at org.bson.json.JsonReader.visitExtendedJSON(JsonReader.java:570)
at org.bson.json.JsonReader.readBsonType(JsonReader.java:145)
at org.bson.codecs.BsonDocumentCodec.decode(BsonDocumentCodec.java:82)
at org.bson.codecs.BsonDocumentCodec.decode(BsonDocumentCodec.java:41)
at org.bson.codecs.BsonDocumentCodec.readValue(BsonDocumentCodec.java:101)
at org.bson.codecs.BsonDocumentCodec.decode(BsonDocumentCodec.java:84)
at org.bson.BsonDocument.parse(BsonDocument.java:62)
at io.debezium.connector.mongodb.transforms.UnwrapFromMongoDbEnvelope.apply(UnwrapFromMongoDbEnvelope.java:45)
at org.apache.kafka.connect.runtime.TransformationChain.apply(TransformationChain.java:38)
at org.apache.kafka.connect.runtime.WorkerSourceTask.sendRecords(WorkerSourceTask.java:218)
at org.apache.kafka.connect.runtime.WorkerSourceTask.execute(WorkerSourceTask.java:194)
at org.apache.kafka.connect.runtime.WorkerTask.doRun(WorkerTask.java:170)
at org.apache.kafka.connect.runtime.WorkerTask.run(WorkerTask.java:214)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
$ cat connect-mongo-source.properties
name=mongodb-source-connector
connector.class=io.debezium.connector.mongodb.MongoDbConnector
mongodb.hosts=''
initial.sync.max.threads=1
tasks.max=1
mongodb.name=higee
$ cat elasticsearch.properties
name=elasticsearch-sink
connector.class = io.confluent.connect.elasticsearch.ElasticsearchSinkConnector
tasks.max=1
topics=higee.higee.higee
key.ignore=true
connection.url=''
type.name=kafka-connect
transforms=unwrap
transforms.unwrap.type = io.debezium.connector.mongodb.transforms.UnwrapFromMongoDbEnvelope
ERROR WorkerSinkTask{id=elasticsearch-sink-0} Task threw an uncaught and unrecoverable exception (org.apache.kafka.connect.runtime.WorkerTask:172)
org.bson.BsonInvalidOperationException: Document does not contain key $set
at org.bson.BsonDocument.throwIfKeyAbsent(BsonDocument.java:844)
at org.bson.BsonDocument.getDocument(BsonDocument.java:135)
at io.debezium.connector.mongodb.transforms.UnwrapFromMongoDbEnvelope.apply(UnwrapFromMongoDbEnvelope.java:53)
at org.apache.kafka.connect.runtime.TransformationChain.apply(TransformationChain.java:38)
at org.apache.kafka.connect.runtime.WorkerSinkTask.convertMessages(WorkerSinkTask.java:480)
at org.apache.kafka.connect.runtime.WorkerSinkTask.poll(WorkerSinkTask.java:301)
at org.apache.kafka.connect.runtime.WorkerSinkTask.iteration(WorkerSinkTask.java:205)
at org.apache.kafka.connect.runtime.WorkerSinkTask.execute(WorkerSinkTask.java:173)
at org.apache.kafka.connect.runtime.WorkerTask.doRun(WorkerTask.java:170)
at org.apache.kafka.connect.runtime.WorkerTask.run(WorkerTask.java:214)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
3)更改了test.avsc并运行了logstash。我没有得到任何错误消息,但结果不是我所期望的,因为origin
、salary
、name
字段都是空的,尽管它们被赋予了非空值。我甚至能够正确地通过控制台使用者读取数据。
$ cat test.avsc
>>>
{
"type" : "record",
"name" : "MongoEvent",
"namespace" : "higee.higee",
"fields" : [ {
"name" : "_id",
"type" : {
"type" : "record",
"name" : "HigeeEvent",
"fields" : [ {
"name" : "$oid",
"type" : "string"
}, {
"name" : "salary",
"type" : "long"
}, {
"name" : "origin",
"type" : "string"
}, {
"name" : "name",
"type" : "string"
} ]
}
} ]
}
$ cat logstash3.conf
>>>
input {
kafka {
bootstrap_servers => ["localhost:9092"]
topics => ["higee.higee.higee"]
auto_offset_reset => "earliest"
codec => avro {
schema_uri => "./test.avsc"
}
}
}
output {
stdout {
codec => rubydebug
}
}
$ bin/logstash -f logstash3.conf
>>>
{
"@version" => "1",
"_id" => {
"salary" => 0,
"origin" => "",
"$oid" => "",
"name" => ""
},
"@timestamp" => 2018-04-25T09:39:07.962Z
}
您必须使用Avro使用者,否则您将得到'UTF-8'codec can't decode byte
即使这个示例也不会起作用,因为您仍然需要模式注册表来查找模式。
Confluent的Python客户端的先决条件说它可以与Python3.x一起工作
$oid
来代替_id
您的AVSC实际上应该如下所示
{
"type" : "record",
"name" : "MongoEvent",
"namespace" : "higee.higee",
"fields" : [ {
"name" : "_id",
"type" : {
"type" : "record",
"name" : "HigeeEvent",
"fields" : [ {
"name" : "$oid",
"type" : "string"
}, {
"name" : "salary",
"type" : "long"
}, {
"name" : "origin",
"type" : "string"
}, {
"name" : "name",
"type" : "string"
} ]
}
} ]
}
但是,Avro不允许任何名称以[A-Za-z_]
的正则表达式开头,因此$oid
将是一个问题。
虽然我并不推荐它(实际上也没有尝试过),但一种可能的方法是使用Pipe input插件将JSON编码的Avro数据从Avro控制台消费者获取到Logstash中
input {
pipe {
codec => json
command => "/path/to/confluent/bin/kafka-avro-console-consumer --bootstrap-server localhost:9092 --topic higee.higee.higee --from-beginning"
}
}
http://debezium.io/docs/connectors/mongodb/
我想这也适用于patch
值,但我不知道Debezium,真的。
如果不使用简单的消息转换(SMT),Kafaka就不会解析正在运行的JSON。阅读链接到的文档后,您可能应该将这些内容添加到连接源属性中
transforms=unwrap
transforms.unwrap.type=io.debezium.connector.mongodb.transforms.UnwrapFromMongoDbEnvelope
如果我没记错的话,Connect将只对顶级Avro字段应用Elasticsearch映射,而不是嵌套的字段。
换句话说,生成的映射遵循这种模式,
"patch": {
"string": "...some JSON object string here..."
},
您实际上需要这样做--可能手动定义您的ES索引
"patch": {
"properties": {
"_id": {
"properties" {
"$oid" : { "type": "text" },
"name" : { "type": "text" },
"salary": { "type": "int" },
"origin": { "type": "text" }
},
我有一个kafka主题,有200万条消息,我的刷新大小是100000,默认分区为分布式模式,有4个工作者,我可以看到数据在几秒钟内立即写入HDFS(10到15秒)。 我看到创建了一个+tmp目录和文件夹,并且每次触发一个新连接器时都会创建主题。 kafka connect的行为是每次都写得这么快,还是已经将数据存储在HDFS中,并根据连接器属性将其移动到主题目录? 我需要清楚这是怎么发生的。如果我
我有一个生产者,它正在为一个主题生成protobuf消息。我有一个消费者应用程序,它反序列化protobuf消息。但hdfs接收器连接器直接从Kafka主题接收消息。中的键和值转换器将设置为什么?做这件事最好的方法是什么?提前道谢!
我想知道有没有办法 > 每个架构而不是每个表创建主题。如果启用了每个模式的主题,那么是否可以在表的基础上支持模式演进(使用模式注册表)? 如果每个模式的主题是不可能的,那么有没有关于如何管理100个或数千个主题的指导方针?考虑到表数与主题数之间会有一对一的映射?
我设置了一个Kafka JDBC接收器以将事件发送到PostgreSQL。我编写了这个简单的生产者,它将带有模式(avro)数据的JSON发送到一个主题,如下所示: producer.py(kafka-python) 价值架构: 连接器配置(无主机、密码等) 但我的连接器出现严重故障,有三个错误,我无法找出其中任何一个错误的原因: TL;博士;日志版本 完整日志 有人能帮我理解这些错误和潜在的原因
我有Kafka主题,有多种类型的消息流入并使用Kafka Connect写入弹性搜索。流看起来不错,直到我不得不将唯一的消息集分离到唯一的索引中。也就是说,我必须根据字段(JSON消息)为新的数据集获取新的索引。 我如何配置/定制Kafka connect以实现同样的功能?每个消息都包含一个表示消息类型和时间戳的字段。 示例 Json 如下所示: Sample1: {“log”:{“data”:“
我使用自己的自定义Sink插件运行Kafka Connect集群(本地有1个工人Docker Compose)。我想在连接器中使用几个主题:topicA、topicB、topicC,每个主题都有一个分区。 我的连接器启动时的配置子集如下: 使用此配置,我希望Kafka Connect为每个接收器任务分配一个主题,但遗憾的是,这不是我看到的。实践中发生的情况是,为分配了所有主题的每个任务调用Sink