Am trying to get realtime data of topoloiges running in Apache Storm using Elasticsearch APM.
During topology submission, am passing required arguments like -Delastic.apm.service_name, -Delastic.apm.server_url, -Delastic.apm.application_packages & javaagent.
Topologies are also running and i can see required parameters in topology process. Topologies are processing data but no data is coming to APM.
Can someone help me on this? Am I missing some arguments or Storm is not supported or something different?
Has anyone configured APM on Apache Storm or Spark?
Related
I want to have a view of Spark in Kibana such as decommissioned nodes per application, shuffle read and write per application, and more.
I know I can get all this information about these metrics here.
But I don't know how to send them to elastic search or how to do it the correct way. I know I can do it with Prometheus but I don't think that helps me.
Is there a way of doing so?
How to configure Filebeats to read apache spark application log. The logs generated is moved to history server, in non readable format as soon as the application is completed. What is the ideal way here.
You can configure Spark logging via Log4J. For a discussion around some edge cases for setting up log4j configuration, see SPARK-16784, but if you simply want to collect all application logs coming off a cluster (vs logs per job) you shouldn't need to consider any of that.
On the ELK side, there was a log4j input plugin for logstash, but it is deprecated.
Thankfully, the documentation for the deprecated plugin describes how to configure log4j to write data locally for FileBeat, and how to set up FileBeat to consume this data and sent it to a Logstash instance. This is now the recommended way to ship logs from systems using log4j.
So in summary, the recommended way to get logs from Spark into ELK is:
Set the Log4J configuration for your Spark cluster to write to local files
Run FileBeat to consume from these files and sent to logstash
Logstash will send data into Elastisearch
You can search through your indexed log data using Kibana
I am searching a distributed real-time computing system that will collect data from a kafka server in order to process the data and then to store it in ElasticSearch. I already selected some of them:
Apache Storm
Apache Spark Streaming
and Logstash (which is more descripted as an ETL (Extract, Transform, load))
I already found several tutorials comparing Storm and Spark Streaming. However, I did not find any tutorial comparing logstash to storm and spark streaming. This is very confusing for me because I am already familiar with logstash but I want to be sure that I select the right tool for my needs.
Thank you in advance
Logstash is a data collection engine with real-time capabilities. It supports analysis, archiving, monitoring, alerting..based on some pre-defined metrics.
--> Logstash is a kind of specific product, solution
Apache Spark and Storm are very general distributed real-time computation systems.
--> Apache Spark/Storm are just frameworks/libraries for general purposes.
I am just a newbie in Big Data world, so I do not know how to build a dashboard application for visualizing data from log files in Hadoop. After searching around, I can think of some solution:
1/ Using Kafka to ingesting streaming data
2/ Stream data processing: Streaming Spark or Apache Flink
3/ Front-end --> Visualize data: using d3js
Am I missing something? Spark and Flink which one should I use?
I have a cluster of machines, I've installed Ambari, HDP 2.4.2, HDFS 2.7, YARN 2.7, Spark 1.6, Kafka.
If possible, could you guys show me some tutorials to build such a application like that? Any book or course?
Thank a lot.
P/s:
I have read the git book of databrick, but it's only mentioned spark. I also find some tutorials how to analyze using Flink, Elasticsearch and Kibana, but it's not mentioned about how to combine with Ambari Server, that where I got stuck
You may take a look at Ambari Log Search feature: https://github.com/abajwa-hw/logsearch-service which visualizes the logs.
We have a huge existing application in php which
Accepts a log file
Initialises all the database, in-memory store resources
Processes every line
Creates a set of output files
Above process happens per input file.
Input files are written by a kafka consumer. Is it possible to fit this application in spark streaming by somehow not porting all the code in java? For example in following manner
get a message from kafka topic
Pass this message to spark streaming
Spark streaming somehow interacts with legacy app and generates output
spark then writes output again in kafka
Whatever I have just mentioned is too high level. I just want to know whether there's a possibility of doing this by not recoding existing app in java? And can anyone please tell me roughly how this can be done?
I think there is no possibility to use PHP in Spark directly. According to documentation (http://spark.apache.org/) and my knowledge it supports only Java, Scala, R and Python.
However you can change an architecture of your app and create some external services (ws, rest etc) and use them from Spark (you can use whichever library you want) - not all modules from old app must be rewritten to Java. I would try to go in that way :)
I think Storm is an excellent choice in this case because it offers non-jvm language integration through Thrift. Also I am sure that there is a PHP Thrift client.
So basically what you have to do is finding a ShellSpout and ShellBolt written in PHP (this is the integration part needed to interact with Storm in your application) and then write your own spouts and bolts which are consuming Kafka and processing each line.
You can use this library for your need:
https://github.com/Lazyshot/storm-php
Then you will also have to find a PHP Thrift client to interact with the Storm cluster.
The Storm Thrift definition can be found here:
https://github.com/apache/storm/blob/master/storm-core/src/storm.thrift
And a PHP Thrift client example can be found here:
https://thrift.apache.org/tutorial/php
Now putting these things together you can write your own Apache Storm app in PHP.
Information sources:
http://storm.apache.org/about/multi-language.html
http://storm.apache.org/releases/current/Using-non-JVM-languages-with-Storm.html