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SQL Interview Success: Unlocking the Top 5 Frequently Asked Queries

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 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

Cloudera Impala top features useful for developers

Cloudera Impala that runs on Apache Hadoop. The program was proclaimed in October 2012 with a common beta trial dispersion. Popular usage is in data analytics.The key features useful for interviews. Impala The Apache-licensed Impala program begets scalable collateral database techniques to Hadoop, authorizing consumers to subject low-latency SQL requests to information kept in HDFS and Apache HBase short of needing information motion either alteration. Impala is amalgamated with Hadoop to employ the similar file and information setups, metadata, safeguarding and asset administration architectures applied by MapReduce, Apache Hive, Apache Pig and different Hadoop code. Impala Applications Impala is advanced for experts and information experts in science to accomplish systematic computational analysis of data or statistics on information kept in Hadoop through SQL either trade intellect implements.    The effect is that extensive information handling (via MapReduce) and two-way req