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5 Super SEO Blogger Tools

In this post, I have explained top blogging tools that need to be considered by every blogger. These tools help you write better SEO friendly blog posts.



1). Headline Analyzer The best tool is the EMV Headline Analyzer. When you enter the headline it analyzes it and gives you EMV ranking. When you get '50' and above it performs better SEO.

2). Headline Length Checker The usual headline length is 50 to 60 characters. Beyond that, the headline will get truncated and looks ugly for search engine users. The tool SERP Snippet Optimization Tool useful to know how it appears in the search results.

3). Free Submission to Search Engines The tool Ping-O-Matic is a nice free submission tool. After your blog post, you can submit your feed to Ping-O-Matic. It submits to search engines freely.

4). Spell and Grammar Check Another free tool is Grammarly, this tool checks your spelling and grammar mistakes. So that you can avoid small mistakes.

5). Keyword AnalyzerWordstream Keyword analyzer i…

Big Data:Top Hadoop Interview Questions (2 of 5)

Frequently asked Hadoop interview questions.


1. What is Hadoop?Hadoop is a framework that allows users the power of distributed computing.

2.What is the difference between SQL and Hadoop?

SQL is allowed to work with structured data. But SQL is most suitable for legacy technologies. Hadoop is suitable for unstructured data. And, it is well suited for modern technologis.
Hadoop

3. What is Hadoop framework?

It is distributed network of commodity servers(A server can contain multiple clusters, and a cluster can have multiple nodes)

4. What are 4 properties of Hadoop?

Accessible-Hadoop runs on large clusters of commodity machinesRobust-An assumption that low commodity machines cause many machine failures. But it handles these tactfully. Scalable-Hadoop scales linearly to handle larger data by adding more nodes to the cluster. Simple-Hadoop allows users to quickly write efficient parallel code

5. What kind of data Hadoop needs?

Traditional RDBMS having relational structure with data resides in tables. In Hadoop. data should be in Key,Value pair.

6. Is Hadoop suitable for on the fly processing?

Hadoop is not suitable. It is suitable only for off-line processing. That means, we can not use Hadoop on active web logs. We can use it on web logs data,which already generated. So, in this property Hadoop is matching to traditional data warehouses.

7. What is Map reduce?

Map reduce is a data processing model, which contain mappers, and reducers. It takes unstructred data as input, and create as Key,Value pairs for processing on Hadoop.

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Tokenization story you need Vault based Vs Vault-less

The term tokenization refers to create a numeric or alphanumeric number in place of the original card number. It is difficult for hackers to get original card numbers.

Vault-Tokenization is a concept a Vault server create a new Token for each transaction when Customer uses Credit or Debit Card at Merchant outlets 
Let us see an example,  data analysis. Here, card numbers masked with other junk characters for security purpose.

Popular Tokenization ServersThere are two kinds of servers currently popular for implementing tokenization.
Vault-based Vault-less Video Presentation on Tokenization
Vault-based server The term vault based means both card number and token will be stored in a Table usually Teradata tables. During increasing volume of transactions, the handling of Table is a big challenge.
Every time during tokenization it stores a record for each card and its token. When you used a card multiple times, each time it generates multiple tokens. It is a fundamental concept.
So the challe…