HiveWhat is Hive?

Hive is a data warehouse system for Hadoop that facilitates easy data summarization, ad-hoc queries, and the analysis of large datasets stored in Hadoop compatible file systems.

Hive was originally developed at Facebook. It’s now a Hadoop subproject with many contributors. Users need to concentrate only on the top level hive language rather than java map reduce programs. One of the main advantages of Hive is its SQLish nature. Thus it leverages the usability to a higher extend.

A hive program will be automatically compiled into map-reduce jobs executed on Hadoop. In addition, HiveQL supports custom map-reduce scripts to be plugged into queries.

Hive example:

selecting the employee names whose salary more than 100 dollars from a hive table called tbl_employee.

SELECT employee_name FROM tbl_employee WHERE salary > 100;

Users are excited to use Hive since it is very similar to SQL.

What are the types of tables in Hive?

There are two types of tables.

1. Managed tables.

2. External tables.

Only the drop table command differentiates managed and external tables. Otherwise, both type of tables are very similar.

Does Hive support record level Insert, delete or update?

Hive does not provide record-level update, insert, or delete. Henceforth, Hive does not provide transactions too. However, users can go with CASE statements and built in functions of Hive to satisfy the above DML operations. Thus, a complex update query in a RDBMS may need many lines of code in Hive.

What kind of datawarehouse application is suitable for Hive?

Hive is not a full database. The design constraints and limitations of Hadoop and HDFS impose limits on what Hive can do.

Hive is most suited for data warehouse applications, where

1) Relatively static data is analyzed,

2) Fast response times are not required, and

3) When the data is not changing rapidly.

Hive doesn’t provide crucial features required for OLTP, Online Transaction Processing. It’s closer to being an OLAP tool, Online Analytic Processing.So, Hive is best suited for data warehouse applications, where a large data set is maintained and mined for insights, reports, etc.

How can the columns of a table in hive be written to a file?

By using awk command in shell, the output from HiveQL (Describe) can be written to a file.

hive -S -e “describe table_name;” | awk -F” ” ’{print 1}’ > ~/output.


CONCAT function in Hive with Example?

CONCAT function will concat the input strings. You can specify any number of strings separated by comma.


CONCAT (‘Hive’,’-‘,’performs’,’-‘,’good’,’-‘,’in’,’-‘,’Hadoop’);



So, every time you delimit the strings by ‘-‘. If it is common for all the strings, then Hive provides another command CONCAT_WS. Here you have to specify the delimit operator first.

CONCAT_WS (‘-‘,’Hive’,’performs’,’good’,’in’,’Hadoop’);

Output: Hive-performs-good-in-Hadoop

REPEAT function in Hive with example?

REPEAT function will repeat the input string n times specified in the command.






Note: You can add a space with the input string also.

TRIM function in Hive with example?

TRIM function will remove the spaces associated with a string.


TRIM(‘  Hadoop  ‘);





Note: If you want to remove only leading or trialing spaces then you can specify the below commands respectively.

LTRIM(‘  Hadoop’);

RTRIM(‘Hadoop  ‘);


REVERSE function in Hive with example?

REVERSE function will reverse the characters in a string.








LOWER or LCASE function in Hive with example?

LOWER or LCASE function will convert the input string to lower case characters.









If the characters are already in lower case then they will be preserved.

UPPER or UCASE function in Hive with example?

UPPER or UCASE function will convert the input string to upper case characters.








If the characters are already in upper case then they will be preserved.

Double type in Hive – Important points?

It is important to know about the double type in Hive. Double type in Hive will present the data differently unlike RDBMS.

See the double type data below:





E5 represents 10^5 here. So, the value 3.99893E5 represents 399893. All the calculations will be accurately performed using double type. The maximum value for a IEEE 754 double is about 2.22E308.

It is crucial while exporting the double type data to any RDBMS since the type may be wrongly interpreted. So, it is advised to cast the double type into appropriate type before exporting.

Rename a table in Hive – How to do it?

Using ALTER command, we can rename a table in Hive.

ALTER TABLE hive_table_name RENAME  TO new_name;

There is another way to rename a table in Hive. Sometimes, ALTER may take more time if the underlying table has more partitions/functions. In that case, Import and export options can be utilized. Here you are saving the hive data into HDFS and importing back to new table like below.

EXPORT TABLE tbl_name TO ‘HDFS_location’;

IMPORT TABLE new_tbl_name FROM ‘HDFS_location’;

If you prefer to just preserve the data, you can create a new table from old table like below.

CREATE TABLE new_tbl_name AS SELECT * FROM old_tbl_name;

DROP TABLE old_tbl_name;

How to change a column data type in Hive?

ALTER TABLE table_name CHANGE column_name column_name new_datatype;

Example: If you want to change the data type of ID column from integer to bigint in a table called employee.


Difference between order by and sort by in hive?

SORT BY will sort the data within each reducer. You can use any number of reducers for SORT BY operation.

ORDER BY will sort all of the data together, which has to pass through one reducer. Thus, ORDER BY in hive uses single reducer.

ORDER BY guarantees total order in the output while SORT BY only guarantees ordering of the rows within a reducer. If there is more than one reducer, SORT BY may give partially ordered final results

RLIKE in Hive?

RLIKE (Right-Like) is a special function in Hive where if any substring of A matches with B then it evaluates to true. It also obeys Java regular expression pattern. Users don’t need to put % symbol for a simple match in RLIKE.


‘Express’ RLIKE ‘Exp’ –> True

‘Express’ RLIKE ‘^E.*’ –> True (Regular expression)

Moreover, RLIKE will come handy when the string has some spaces. Without using TRIM function, RLIKE satisfies the required scenario. Suppose if A has value ‘Express ‘ (2 spaces additionally) and B has value ‘Express’ RLIKE will work better without using TRIM.

‘Express’ RLIKE ‘Express’ –> True


RLIKE evaluates to NULL if A or B is NULL.