Hive SQL Based Datawarehouse app built on top of hadoop(select,join,groupby…..) It is a platform used to develop SQL type scripts to do MapReduce operations. PARTITIONING Partition tables changes how HIVE structures the data storage *Used for distributing load horizantally ex: PARTITIONED BY (country STRING, state STRING); A subset of a table’s data set where one column has the same value for all records in the subset. In Hive, as in most databases […]
This post is about basic String Functions in Hive with syntax and examples. Creating Table in HIVE:
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hive> create external table Tri100(id int,name string,location varchar(30),sal int,Hike int) > row format delimited > fields terminated by ',' > lines terminated by '\n' > stored as textfile location '/Jayanth/Jay/'; |
String Functions and Normal Queries:
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hive> select * from Tri100; 1 rahul Hyderabad 30000 40000 2 Mohit Banglore 22000 25000 3 Rohan Banglore 33000 40000 4 Ajay Bangladesh 40000 45000 5 srujay Srilanka 25000 30000 |
ASCII ASCII Function converts the first character of the string into its numeric ASCII value.
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hive> select ASCII(‘hadoop’) from Tri100 where sal=22000; 104 hive> select ASCII(‘Hadoop’) from Tri100 where sal=22000; 72 hive> select ASCII(‘A’) from Tri100 where sal=22000; 65 |
CONCAT The CONCAT function concatenates all the strings/columns.
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hive> select CONCAT(name,'+',location) from Tri100; rahul+Hyderabad Mohit+Banglore Rohan+Banglore Ajay+Bangladesh srujay+Srilanka |
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hive> select concat(name,'+',sal) from Tri100; rahul+30000 Mohit+22000 Rohan+33000 Ajay+40000 srujay+25000 |
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hive> select CONCAT(name,' ','Got Hike of',' ',Hike,' ','from',' ',sal) from Tri100; rahul Got Hike of 40000 from 30000 Mohit Got Hike of 25000 from 22000 Rohan Got Hike of 40000 from 33000 Ajay Got Hike of 45000 from 40000 srujay Got Hike of 30000 from 25000 |
CONCAT_WS Syntax: “CONCAT_WS(string delimiter, string str1,str2……)" The CONCAT_WS function concatenates all the strings only strings and Column with datatype string.
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hive> select CONCAT_WS('+',name,location) from Tri100; rahul+Hyderabad Mohit+Banglore Rohan+Banglore Ajay+Bangladesh srujay+Srilanka |
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Creating Table in HIVE :
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hive> create external table Tri100(id int,name string,location varchar(30),sal int,Hike int) > row format delimited > fields terminated by ',' > lines terminated by '\n' > stored as textfile location '/Jayanth/Jay/'; |
Aggregated Functions and Normal Queries:
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hive> select * from Tri100; OK 1 rahul Hyderabad 3000 40000 2 Mohit Banglore 22000 25000 3 Rohan Banglore 33000 40000 4 Ajay Bangladesh 40000 45000 5 srujay Srilanka 25000 30000 Time taken: 0.184 seconds, Fetched: 5 row(s) |
SUM Returns the sum of the elements in the group or sum of the distinct values of the column in the group.
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hive> select sum(sal) from Tri100; OK 150000 Time taken: 17.909 seconds, Fetched: 1 row(s) hive> select Sum(sal) from Tri100 where loccation='Banglore'; OK 55000 Time taken: 18.324 seconds, Fetched: 1 row(s) |
Count count(*) – Returns the total number of retrieved rows, including rows containing NULL values; count(expr) – Returns the number of rows for which the supplied expression is non-NULL; count(DISTINCT expr[, expr]) – Returns the […]
HIVE Date Functions from_unixtime: This function converts the number of seconds from unix epoch (1970-01-01 00:00:00 UTC) to a STRING that represents the TIMESTAMP of that moment in the current system time zone in the format of “1970-01-01 00:00:00”. The following example returns the current date including the time.
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hive> SELECT FROM_UNIXTIME(UNIX_TIMESTAMP()); OK 2015-05-18 05:43:37 Time taken: 0.153 seconds, Fetched: 1 row(s) |
from_utc_timestamp This function assumes that the string in the first expression is UTC and then, converts that string to the […]
Hive Functions Examples SET SHOW USE CREATE DATABASE CREATE MANAGED TABLE CREATE EXTERNAL TABLE CREATING TABLE FROM EXISTING TABLE CREATING EXTERNAL TABLES FROM MANAGED TABLES LOAD COPY DATA FROM ONE TABLE TO ANOHTER DROP QUIT SELECT DESCRIBE DESCRIBE SPECIFIC FIELD DESCRIBE EXTENDED ALTER CLONE SCHEMA (DATA IS NOT COPIED) CLONE SCHEMA TO ANOTHER DB USING REGULAR EXPRESSIONS MATHEMATICAL FUNCTIONS AGGREGATE FUNCTIONS LIMIT NESTED SELECT STATEMENT CASE..WHEN..THEN LIKE & RLIKE JOINS […]
In our previous post we have discussed about hadoop job optimization or Hadoop Performance Tuning for Mapreduce jobs. In this post we will briefly discuss a few points on how to optimize hive queries/ Hive Performance tuning. If we do not fine tune Hive properly, then even for select queries on smaller tables in Hive, some times it may take minutes to emit results. So, because of this reason Hive […]
