There is a requirement where we get a stream of data from Kafka Stream and our objective is to push this data to SOLR.
We did some reading but we could find there are lot of Kafka Connect solutions available in the market, but the problem is we do not know which is the best solution and how to achieve.
The options are:
Use Solr connector to connect with Kafka.
Use Apache Storm as it directly provides support for integrating with Solr.
There is no much documentation or in depth information provided for the above mentioned options.
Will anyone be kind enough to let me know
How we can use a Solr connector and integrate with Kafka stream without using Confluent?
Solr-Kafka Connector: https://github.com/MSurendra/kafka-connect-solr
Also, With regard to Apache Storm,
will it be possible for Apache Storm to accept the Kafka Stream and push it to Solr, though we would need some sanitization of data before pushing it to Solr?
I am avoiding Storm here, because the question is mostly about Kafka Connect
CAVEAT - This Solr Connector in the question is using Kakfa 0.9.0.1 dependencies, therefore, it is very unlikely to work with the newest Kafka API's.
This connector is untested by me. Follow at your own risk
The following is an excerpt from Confluent's documentation on using community connectors, with some emphasis and adaptations. In other words, written for Kafka Connects not included in Confluent Platform.
1) Clone the GitHub repo for the connector
$ git clone https://github.com/MSurendra/kafka-connect-solr
2) Build the jar with maven
Change into the newly cloned repo, and checkout the version you want. (This Solr connector has no releases like the Confluent ones).
You will typically want to checkout a released version.
$ cd kafka-connect-solr; mvn package
From here, see Installing Plugins
3) Locate the connector’s uber JAR or plugin directory
We copy the resulting Maven output in the target directory into one of the directories on the Kafka Connect worker’s plugin path (the plugin.path property).
For example, if the plugin path includes the /usr/local/share/kafka/plugins directory, we can use one of the following techniques to make the connector available as a plugin.
As mentioned in the Confluent docs, the export CLASSPATH=<some path>/kafka-connect-solr-1.0.jar option would work, though plugin.path will be the way moving forward (Kafka 1.0+)
You should know which option to use based on the result of mvn package
Option 1) A single, uber JAR file
With this Solr Connector, we get a single file named kafka-connect-solr-1.0.jar.
We copy that file into the /usr/local/share/kafka/plugins directory:
$ cp target/kafka-connect-solr-1.0.jar /usr/local/share/kafka/plugins/
Option 2) A directory of dependencies
(This does not apply to the Solr Connector)
If the connector’s JARs are collected into a subdirectory of the build’s target directories, we can copy all of these JARs into a plugin directory within the /usr/local/share/kafka/plugins, for example
$ mkdir -p /usr/local/share/kafka/plugins/kafka-connect-solr
$ cp target/kafka-connect-solr-1.0.0/share/java/kafka-connect-solr/* /usr/local/share/kafka/plugins/kafka-connect-solr/
Note
Be sure to install the plugin on all of the machines where you’re running Kafka Connect distributed worker processes. It is important that every connector you use is available on all workers, since Kafka Connect will distribute the connector tasks to any of the worker
4) Running Kafka Connect
If you have properly set plugin.path or did export CLASSPATH, then you can use connect-standalone or connect-distributed with the appropriate config file for that Connect project.
Regarding,
we would need some sanitization of data before pushing it to Solr
You would need to do that with a separate process like Kafka Streams, Storm, or other process prior to Kafka Connect. Write your transformed output to a secondary topic. Or write your own Kafka Connect Transform process. Kafka Connect has very limited transformations out of the box.
Also worth mentioning - JSON seems to be the only supported Kafka message format for this Solr connector
Related
In Spark, instead of building a fat-jar, we are able to upload third-party dependencies required for my job via --jars.
Similarly, I am able to upload the configuration files needed for my job via --files.
But in Flink, I checked --help and didn't find a similar option.
So:
For dependent jars, is here a way to load third-party dependencies for jobs on-demand without modifying the cluster environment? (The required third-party dependencies may be different for different jobs)
For the configured files, is there a way to upload them like --files? And how do I read it?
Thanks.
additional
When use flink run to submit a job to yarn-per-job, I can read my local-file in flink.
But when using flink run-application, I tried a variety of ways, are unable to get to read the local-file, there is any way to go to the it.
I am using yarn. Flink version: 1.14
I am looking for integrating Apache Atlas with Apache Flink to capture Job lineage. I found some references around it from Cloudera (CDP) and they are using Atlas-flink hook , But not able to find any documentation or implementation without CDP and Atlas-Flink connection JAR as well.
Let me know if anyone has done integration between them?
I am newbie in Apache Flink and our team is trying to set up an Apache Flink Cluster on Apaches Mesos. We have already installed Apache Mesos & Marathon with 3 Master nodes and 3 Slaves and now we are trying to install Apache Flink without DC/OS as mentioned here https://ci.apache.org/projects/flink/flink-docs-release-1.3/setup/mesos.html#mesos-without-dcos.
I have couple of questions over here :
Do we need to download Flink on all the nodes(master and slaves) and configure mesos.master in all nodes?
Or Shall we download flink on only one master node and configure mesos.master over there?
If flink needs to be downloaded on all the nodes then what should be the location of flink directory or if there is any script where I can specify that?
Is running "mesos-appmaster.sh" on master node also responsible for running flink libraries and classes on slaves?
Thanks
Do we need to download Flink on all the nodes(master and slaves) and configure mesos.master in all nodes?
No you don't. Actualy it depends on the way you want to run Flink. In your setup the most convenient way to run Flink would be to run it with Marathon and download binaries during deployment. See this
Or Shall we download flink on only one master node and configure mesos.master over there?
It's up to you. You can run Flink on dedicated server or let Marathon do it for you. If you already have Marathon then it's easier to run Flink with Marathon. On the other hand for debugging purposes and proof of concept I'll recommend standalone version where you can quickly change configuration on local machine and see how it works. Creating docker images or binaries and publishing them in repository and finally deploying Flink on Marathon could have more overhead that will slow you down on development but will keep you safe on production. Flink does not come with support for High Availability (HA) so Marathon is required to provide basic HA support (launch new instance of Flink when agent crash).
If flink needs to be downloaded on all the nodes then what should be the location of flink directory or if there is any script where I can specify that?
Flink does not have to be downloaded on all nodes. It can be downloaded when needed at deployment.
Is running "mesos-appmaster.sh" on master node also responsible for running flink libraries and classes on slaves?
Flink is a scheduler which means that it should start tasks and executors on Mesos when needed.
Even when not using DC/OS, feel free to look at the Apache Flink DC/OS package. At its core, it is a marathon app definition you can deploy on pure Marathon/Mesos. The Flink package (as of today) does not require any DC/OS specific features.
The DC/OS example might also provide useful information.
I'm new to Apache solr and I want to index data from kafka into solr. Can anyone give simple example of doing this ?
The easiest way to get started on this would probably be to use Kafka Connect.
Connect is part of the apache Kafka package, so should already be installed on your Kakfa node(s). Please refer to the quickstart for a brief introduction on how to run connect.
For writing data to Solr there are two connectors that you could try:
https://github.com/jcustenborder/kafka-connect-solr
https://github.com/MSurendra/kafka-connect-solr
While I don't have any experience with either of them, I'd probably try Jeremy's first based on latest commit and the fact that he works for Confluent.
We have a clustered environment where same camel ftp endpoint is installed on multiple fuse instances. I want message(file) to be consumed by only one fuse instance. I am planning to achieve this by implementing IdempotentRepository interface with database persistence. Want to make sure that this approach will work or there is a better way to do it?
If you don't want to depend on a database for doing this you could try with Hazelcast. Hazelcast is a distributed data cache that can be used as a idempotent repository without external dependencies. Also, Apache Camel provides a class for doing this. There is a nice tutorial explaining how to do it: Hazelcast Idempotent Repository Tutorial