The Replicat was kapput: GGSCI (localhost.localdomain) 3> info rkconnoe REPLICAT RKCONNOE Last Started 2017-09-12 17:06 Status ABENDED Checkpoint Lag 00:00:00 (updated 00:46:34 ago) Log Read Checkpoint File /u01/app/ogg/dirdat/oe000000 First Record RBA 0 So checking the OGG error log ggserr.log showed 2017-09-12T17:06:17.572-0400 ERROR OGG-15051 Oracle GoldenGate Delivery, rkconnoe.prm: Java or JNI exception: oracle.goldengate.util.GGException: Error detected handling operation added event. 2017-09-12T17:06:17.572-0400 ERROR OGG-01668 Oracle GoldenGate Delivery, rkconnoe.prm: PROCESS ABENDING. So checking the replicat log dirrpt/RKCONNOE_info_log4j.

An error that I see coming up frequently in the Kafka Connect community (e.g. mailing list, Slack group, StackOverflow) is: JsonDeserializer with schemas.enable requires "schema" and "payload" fields and may not contain additional fields or No fields found using key and value schemas for table: foo-bar You can see an explanation, and solution, for the issue in my StackOverflow answer here: https://stackoverflow.com/a/45940013/350613 If you’re using schemas.enable in the Connector configuration, you must have schema and payload as the root-level elements of your JSON message ( Which is pretty much verbatim what the error says 😁), like this:

Kafka’s Connect API is a wondrous way of easily bringing data in and out of Apache Kafka without having to write a line of code. By choosing a Connector from the many available, it’s possible to set up and end-to-end data pipeline with just a few lines of configuration. You can configure this by hand, or you can use the Confluent Control Center, for both management and monitoring: BUT … there are times when not all goes well - perhaps your source has gone offline, or one of your targets has been misconfigured.

tl;dr Make sure that key.converter.schema.registry.url and value.converter.schema.registry.url are specified, and that there are no trailing whitespaces. I’ve been building on previous work I’ve done with Oracle GoldenGate and Kafka Connect, looking at how to have the change records from the Oracle database come through to Kafka in Avro format rather than the default JSON that the sample configuration gives. Simply changing the Kafka Connect OGG configuration file (confluent.properties) from value.converter=org.apache.kafka.connect.json.JsonConverter key.

I hit this error running Kafka Connect HDFS connector from Confluent Platform v3.1.1 on BigDataLite 4.6: [oracle@bigdatalite ~]$ connect-standalone /etc/schema-registry/connect-avro-standalone.properties /etc/kafka-connect-hdfs/quickstart-hdfs.properties [...] Exception in thread "main" java.lang.IncompatibleClassChangeError: Implementing class at java.lang.ClassLoader.defineClass1(Native Method) at java.lang.ClassLoader.defineClass(ClassLoader.java:763) at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142) at java.net.URLClassLoader.defineClass(URLClassLoader.java:467) at java.net.URLClassLoader.access$100(URLClassLoader.java:73) at java.net.URLClassLoader$1.run(URLClassLoader.java:368) at java.net.URLClassLoader$1.run(URLClassLoader.java:362) at java.security.AccessController.doPrivileged(Native Method) at java.net.URLClassLoader.findClass(URLClassLoader.java:361) at java.lang.ClassLoader.loadClass(ClassLoader.java:424) at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:331) at java.lang.ClassLoader.loadClass(ClassLoader.java:357) at java.lang.ClassLoader.defineClass1(Native Method) at java.lang.ClassLoader.defineClass(ClassLoader.java:763) The fix was to unset the CLASSPATH first: unset CLASSPATH

There are various reasons for this error, but the one I hit was that the table name is case sensitive, and returned from Oracle by the JDBC driver in uppercase. If you specify the tablename in your connecter config in lowercase, it won’t be matched, and this error is thrown. You can validate this by setting debug logging (edit etc/kafka/connect-log4j.properties to set log4j.rootLogger=DEBUG, stdout), and observe: (I’ve truncated some of the output for legibility)

I’ve been doing some noodling around with Confluent’s Kafka Connect recently, as part of gaining a wider understanding into Kafka. If you’re not familiar with Kafka Connect this page gives a good idea of the thinking behind it. One issue that I hit defeated my Google-fu so I’m recording it here to hopefully help out fellow n00bs. The pipeline that I’d set up looked like this: Eneco’s Twitter Source streaming tweets to a Kafka topic Confluent’s HDFS Sink to stream tweets to HDFS and define Hive table automagically over them It worked great, but only if I didn’t enable the Hive integration part.