The Impala ORDER BY clause is employed to sort the data in an ascending or descending order, based on one or more columns. Some databases sort the query results in ascending order by default.

Syntax

Following is the syntax of the ORDER BY clause.

select * from table_name ORDER BY col_name [ASC|DESC] [NULLS FIRST|NULLS LAST]

You can arrange the info within the table in ascending or descending order using the keywords ASC or DESC respectively.

In the same way, if we use NULLS FIRST, all the null values within the table are arranged within the top rows; and if we use NULLS LAST, the rows containing null values are going to be arranged last.

Example

Assume we have a table named customers in the database my_db and its contents are as follows −

[quickstart.cloudera:21000] > select * from customers;

Query: select * from customers

+—-+———-+—–+———–+——–+

+—-+———-+—–+———–+——–+

| 3 | kaushik | 23 | Kota | 30000 |

| 1 | Ramesh | 32 | Ahmedabad | 20000 |

| 2 | Khilan | 25 | Delhi | 15000 |

| 6 | Komal | 22 | MP | 32000 |

| 4 | Chaitali | 25 | Mumbai | 35000 |

| 5 | Hardik | 27 | Bhopal | 40000 |

+—-+———-+—–+———–+——–+

Fetched 6 row(s) in 0.51s

Following is an example of arranging the data in the customers table, in ascending order of their id’s using the order by clause.

[quickstart.cloudera:21000] > Select * from customers ORDER BY id asc;

On executing, the above query produces the following output.

Query: select * from customers ORDER BY id asc

+—-+———-+—–+———–+——–+

+—-+———-+—–+———–+——–+

| 1 | Ramesh | 32 | Ahmedabad | 20000 |

| 2 | Khilan | 25 | Delhi | 15000 |

| 3 | kaushik | 23 | Kota | 30000 |

| 4 | Chaitali | 25 | Mumbai | 35000 |

| 5 | Hardik | 27 | Bhopal | 40000 |

| 6 | Komal | 22 | MP | 32000 |

+—-+———-+—–+———–+——–+

Fetched 6 row(s) in 0.56s

In the same way, you can arrange the data of customers table in descending order using the order by clause as shown below.

[quickstart.cloudera:21000] > Select * from customers ORDER BY id desc;

On executing, the above query produces the following output.

Query: select * from customers ORDER BY id desc

+—-+———-+—–+———–+——–+

+—-+———-+—–+———–+——–+

| 6 | Komal | 22 | MP | 32000 |

| 5 | Hardik | 27 | Bhopal | 40000 |

| 4 | Chaitali | 25 | Mumbai | 35000 |

| 3 | kaushik | 23 | Kota | 30000 |

| 2 | Khilan | 25 | Delhi | 15000 |

| 1 | Ramesh | 32 | Ahmedabad | 20000 |

+—-+———-+—–+———–+——–+

Fetched 6 row(s) in 0.54s

Impala – Group By Clause

The Impala GROUP BY clause is employed together with the SELECT statement to rearrange identical data into groups.

Syntax

Following is the syntax of the GROUP BY clause.

select data from table_name Group BY col_name;

Example

Assume we have a table named customers in the database my_db and its contents are as follows −

[quickstart.cloudera:21000] > select * from customers;

Query: select * from customers

+—-+———-+—–+———–+——–+

+—-+———-+—–+———–+——–+

| 1 | Ramesh | 32 | Ahmedabad | 20000 |

| 2 | Khilan | 25 | Delhi | 15000 |

| 3 | kaushik | 23 | Kota | 30000 |

| 4 | Chaitali | 25 | Mumbai | 35000 |

| 5 | Hardik | 27 | Bhopal | 40000 |

| 6 | Komal | 22 | MP | 32000 |

+—-+———-+—–+———–+——–+

Fetched 6 row(s) in 0.51s

You can get the total amount of salary of each customer using GROUP BY query as shown below.

[quickstart.cloudera:21000] > Select name, sum(salary) from customers Group BY name;

On executing, the above query gives the following output.

Query: select name, sum(salary) from customers Group BY name

+———-+————-+

| name | sum(salary) |

+———-+————-+

| Ramesh | 20000 |

| Komal | 32000 |

| Hardik | 40000 |

| Khilan | 15000 |

| Chaitali | 35000 |

| kaushik | 30000 |

+———-+————-+

Fetched 6 row(s) in 1.75s

Assume that this table has multiple records as shown below.

+—-+———-+—–+———–+——–+

+—-+———-+—–+———–+——–+

| 1 | Ramesh | 32 | Ahmedabad | 20000 |

| 2 | Ramesh | 32 | Ahmedabad | 1000| |

| 3 | Khilan | 25 | Delhi | 15000 |

| 4 | kaushik | 23 | Kota | 30000 |

| 5 | Chaitali | 25 | Mumbai | 35000 |

| 6 | Chaitali | 25 | Mumbai | 2000 |

| 7 | Hardik | 27 | Bhopal | 40000 |

| 8 | Komal | 22 | MP | 32000 |

+—-+———-+—–+———–+——–+

Now again, you’ll get the entire amount of salaries of the workers , considering the repeated entries of records, using the Group By clause as shown below.

Select name, sum(salary) from customers Group BY name;

On executing, the above query gives the following output.

Query: select name, sum(salary) from customers Group BY name

+———-+————-+

| name | sum(salary) |

+———-+————-+

| Ramesh | 21000 |

| Komal | 32000 |

| Hardik | 40000 |

| Khilan | 15000 |

| Chaitali | 37000 |

| kaushik | 30000 |

+———-+————-+

Fetched 6 row(s) in 1.75s

Impala – Having Clause

The Having clause in Impala enables you to specify conditions that filter which group results appear within the final results.

In general, the Having clause is employed alongside group by clause; it places conditions on groups created by the GROUP BY clause.

Syntax

Following is the syntax of the Havingclause.

select * from table_name ORDER BY col_name [ASC|DESC] [NULLS FIRST|NULLS LAST]

Example

Assume we have a table named customers in the database my_db and its contents are as follows −

[quickstart.cloudera:21000] > select * from customers;

Query: select * from customers

+—-+———-+—–+————-+——–+

+—-+———-+—–+————-+——–+

| 1 | Ramesh | 32 | Ahmedabad | 20000 |

| 2 | Khilan | 25 | Delhi | 15000 |

| 3 | kaushik | 23 | Kota | 30000 |

| 4 | Chaitali | 25 | Mumbai | 35000 |

| 5 | Hardik | 27 | Bhopal | 40000 |

| 6 | Komal | 22 | MP | 32000 |

| 7 | ram | 25 | chennai | 23000 |

| 8 | rahim | 22 | vizag | 31000 |

| 9 | robert | 23 | banglore | 28000 |

+—-+———-+—–+———–+——–+

Fetched 9 row(s) in 0.51s

Following is an example of using Having clause in Impala −

[quickstart.cloudera:21000] > select max(salary) from customers group by age having max(salary) > 20000;

This query initially groups the table by age and selects the maximum salaries of each group and displays those salaries, which are greater than 20000 as shown below.

20000

+————-+

| max(salary) |

+————-+

| 30000 |

| 35000 |

| 40000 |

| 32000 |

+————-+

Fetched 4 row(s) in 1.30s

So, this brings us to the end of blog. This Tecklearn ‘Explanation of Order by Clause , Group by Clause and Having Clause in Impala’ helps you with commonly asked questions if you are looking out for a job in Big Data and Hadoop Domain.

If you wish to learn Impala and build a career in Big Data or Hadoop domain, then check out our interactive, Big Data Hadoop-Architect (All in 1) Combo Training, that comes with 24*7 support to guide you throughout your learning period. Please find the link for course details:

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