Kafka Exceptions

Kafka is super buzzword nowadays in Bigdata space, so I thought to share some of exceptions and troubleshooting steps that I have encountered till now using Kafka in my project.

Issue 1 # Error while fetching metadata with correlation id 0 : {Visitor=LEADER_NOT_AVAILABLE (org.apache.kafka.clients.NetworkClient)

Fix :  There could be many reason of this failure but I resolved it by updating
                           host.name=localhost
                           advertised.host.name=localhost
        in $Kafka_home/config/server.properties where localhost is kafka’s server                   hostname. Basically it was happening due to incorrect network binding of my               laptop’s wireless interface.

Issue 2 # <Next_Exception_will_be_listed_soon>

What Is Middle Tier Clustering?

Middle tier clustering is just a cluster that is used for service the middle tier in a application. This is popular since many clients may be using middle tier and a lot of heavy load may also be served by middle tier that requires it be to highly available.

Failure of middle tier can cause multiple clients and systems to fail, therefore its one of the approaches to do clustering at the middle tier of a application.

In java world, it is really common to have EJB server clusters that are used by many clients. In general any application that has a business logic that can be shared across multiple client can use a middle tier cluster for high availability.

To reach Big Data take your first step with JSON

Ten years ago, XML was the primary data interchange format. When it came on the scene, it was a breath of fresh air and a vast improvement over the truly appalling SGML (Standard Generalized Markup Language).

But it’s no secret that in the last few years, a bold transformation has been afoot in the world of data interchange. The more lightweight, bandwidth-non-intensive JSON (JavaScript Object Notation) has emerged not just as an alternative to XML, but rather as a potential full-blown successor.The rise of JSON as a key player in database technologies is another bad portent for XML. As it stands, Big Data does not have a preferred data interchange format per se. But the claim that I’d like to make about Big Data and JSON is a bit more specific. What I’d like to argue is that JSON is emerging as a preferred format in web-centric, so-called “NoSQL” databases.

I am putting one JSON example here. you may try to write corresponding XML file and a java Parser for your learning.


{
  "Users": {
    "type": "bank",
    "User": [
      {
        "name": "Ram",
        "Bank": [
          {
            "name": "SBI",
            "UserID": "RamSBI",
            "Password": "RamSBIpwd"
          }
        ]
      },
      {
        "name": "Mohan",
        "Bank": [
          {
            "name": "SBI",
            "UserID": "MohanSBI",
            "Password": "MohanSBIpwd"
          }
        ]
      } 
    ]
  }
}