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SQL Interview Success: Unlocking the Top 5 Frequently Asked Queries

 Here are the five top commonly asked SQL queries in the interviews. These you can expect in Data Analyst, or, Data Engineer interviews. Top SQL Queries for Interviews 01. Joins The commonly asked question pertains to providing two tables, determining the number of rows that will return on various join types, and the resultant. Table1 -------- id ---- 1 1 2 3 Table2 -------- id ---- 1 3 1 NULL Output ------- Inner join --------------- 5 rows will return The result will be: =============== 1  1 1   1 1   1 1    1 3    3 02. Substring and Concat Here, we need to write an SQL query to make the upper case of the first letter and the small case of the remaining letter. Table1 ------ ename ===== raJu venKat kRIshna Solution: ========== SELECT CONCAT(UPPER(SUBSTRING(name, 1, 1)), LOWER(SUBSTRING(name, 2))) AS capitalized_name FROM Table1; 03. Case statement SQL Query ========= SELECT Code1, Code2,      CASE         WHEN Code1 = 'A' AND Code2 = 'AA' THEN "A" | "A

Exclusive Apache Kafka Top Features

Here are the top features of Kafka. It works on the principle of publishing messages. It routes real-time information to consumers far faster. Also, it connects heterogeneous applications by sending messages among them. Here the prime component (a.k.a message router) is a broker. The top features you can read here.

Kafka features

The exclusive Kafka features

The message broker provides seamless integration, but there are two collateral objectives: the first is to not block the producers and the second is to not let the producers know who the final consumers are.

Apache Kafka is a real-time publish-subscribe solution messaging system: open source, distributed, partitioned, replicated, commit-log based with a publish-subscribe schema. Its main characteristics are as follows:

1. Distributed. Cluster

Centric design that supports the distribution of the messages over the cluster members, maintaining the semantics. So you can grow the cluster horizontally without downtime.

2. Multiclient.

Easy integration with different clients from different platforms: Java, .NET, PHP, Ruby, Python, etc.

3. Persistent.

You cannot afford any data lost. Kafka is designed with efficient O(1), so data structures provide constant time performance no matter the data size.

4. Real time.

The messages produced are immediately seen by consumer threads; these are the basis of the systems called complex event processing (CEP).

5. Very high throughput.

As we mentioned, all the technologies in the stack are designed to work in commodity hardware. Kafka can handle hundreds of read and write operations per second from a large number of clients.

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