Pig Latin basics in Hadoop

Introduction

Pig Latin helps you write simple steps to process big data easily. It makes working with large data sets faster and clearer.

You want to clean or filter large data files quickly.

You need to join two big data tables to find connections.

You want to group data to find totals or averages.

You want to sort data to see top or bottom results.

You want to load data from files and save results back.

Syntax

Hadoop

alias = LOAD 'datafile' USING loader AS (field1:type, field2:type, ...);
filtered = FILTER alias BY condition;
grouped = GROUP alias BY field;
result = FOREACH grouped GENERATE group, COUNT(alias);
STORE result INTO 'output';

Each step creates a new alias (name) for the data.

Use LOAD to read data, FILTER to select rows, GROUP to collect by key, FOREACH to process groups, and STORE to save results.

Examples

Load a CSV file with user info, defining each column's name and type.

Hadoop

data = LOAD 'users.csv' USING PigStorage(',') AS (name:chararray, age:int, city:chararray);

Select only users who are 18 or older.

Hadoop

adults = FILTER data BY age >= 18;

Group users by their city.

Hadoop

grouped_by_city = GROUP adults BY city;

Count how many adults are in each city.

Hadoop

count_by_city = FOREACH grouped_by_city GENERATE group, COUNT(adults);

Sample Program

This program loads user data, filters adults, groups them by city, counts adults per city, and shows the result.

Hadoop

users = LOAD 'users.csv' USING PigStorage(',') AS (name:chararray, age:int, city:chararray);
adults = FILTER users BY age >= 18;
grouped = GROUP adults BY city;
count_by_city = FOREACH grouped GENERATE group AS city, COUNT(adults) AS adult_count;
DUMP count_by_city;

Important Notes

Always define the schema (field names and types) when loading data for clarity.

Use DUMP to see results immediately during testing, STORE to save results permanently.

Pig Latin commands run in order, each step uses the previous step's output.

Summary

Pig Latin is a simple language to process big data step-by-step.

Use LOAD, FILTER, GROUP, FOREACH, and STORE to handle data easily.

It helps you clean, group, count, and save big data results quickly.

Practice

1. What is the main purpose of the FILTER statement in Pig Latin?

easy

A. To select rows that meet a condition

B. To combine two datasets

C. To load data from a file

D. To save the results to storage

Solution

1. Step 1: Understand the role of FILTER

   The FILTER statement is used to keep only the rows that satisfy a given condition.

2. Step 2: Compare with other statements

   LOAD reads data, GROUP groups data, STORE saves data, so FILTER is for selecting rows.

3. Final Answer:

   To select rows that meet a condition -> Option A

4. Quick Check:

   FILTER = select rows [OK]

Hint: FILTER keeps rows matching condition, like a sieve [OK]

Common Mistakes:

• Confusing FILTER with GROUP
• Thinking FILTER saves data
• Mixing FILTER with LOAD

2. Which of the following is the correct syntax to load a file named data.txt in Pig Latin?

easy

A. LOAD 'data.txt' USING PigStorage();

B. LOAD data.txt USING PigStorage();

C. LOAD 'data.txt' AS PigStorage();

D. LOAD 'data.txt' USING PigStorage

Solution

1. Step 1: Check the LOAD syntax

   LOAD requires the file path as a string in quotes and the loader function with parentheses.

2. Step 2: Validate each option

   LOAD 'data.txt' USING PigStorage(); uses quotes and parentheses correctly. LOAD data.txt USING PigStorage(); misses quotes. LOAD 'data.txt' AS PigStorage(); uses AS instead of USING. LOAD 'data.txt' USING PigStorage misses parentheses.

3. Final Answer:

   LOAD 'data.txt' USING PigStorage(); -> Option A

4. Quick Check:

   LOAD 'file' USING loader(); [OK]

Hint: LOAD needs quotes and parentheses for loader [OK]

Common Mistakes:

• Forgetting quotes around filename
• Using AS instead of USING
• Omitting parentheses after loader

3. Given the following Pig Latin code:

A = LOAD 'numbers.txt' USING PigStorage(',');
B = FILTER A BY $0 > 10;
C = FOREACH B GENERATE $0;
DUMP C;

What will be the output if numbers.txt contains:
5,abc
15,def
8,ghi
20,jkl

medium

A. (5,abc)
(8,ghi)

B. (5)
(8)

C. (15,def)
(20,jkl)

D. (15)
(20)

Solution

1. Step 1: Understand the FILTER condition

   FILTER keeps rows where first column ($0) is greater than 10, so rows with 15 and 20 remain.

2. Step 2: Understand FOREACH GENERATE

   FOREACH selects only the first column ($0), so output shows only 15 and 20 as single values.

3. Final Answer:

   (15) (20) -> Option D

4. Quick Check:

   FILTER $0 > 10 then select $0 [OK]

Hint: FILTER then FOREACH select column shows filtered values [OK]

Common Mistakes:

• Including second column in output
• Selecting rows less than or equal to 10
• Confusing FILTER condition

4. Identify the error in this Pig Latin script:

data = LOAD 'input.txt' USING PigStorage(',');
filtered = FILTER data BY $1 == 'USA';
grouped = GROUP filtered BY $2;
result = FOREACH grouped GENERATE group, COUNT(filtered);
STORE result INTO 'output';

medium

A. COUNT should use filtered instead of group

B. STORE command missing USING clause

C. FILTER condition uses wrong column index

D. GROUP should use filtered instead of data

Solution

1. Step 1: Check STORE syntax

   STORE requires a USING clause to specify the storage format, e.g., PigStorage().

2. Step 2: Verify other statements

   GROUP uses filtered correctly, COUNT uses filtered correctly, FILTER condition is valid if $1 is country column.

3. Final Answer:

   STORE command missing USING clause -> Option B

4. Quick Check:

   STORE ... INTO 'path' USING loader() [OK]

Hint: STORE needs USING clause to save data [OK]

Common Mistakes:

• Omitting USING in STORE
• Confusing GROUP input
• Misunderstanding COUNT argument

5. You have a dataset of sales with columns: product_id, region, amount. You want to find total sales per region but only for sales above 100. Which Pig Latin sequence correctly achieves this?

hard

A. A = LOAD 'sales.txt' USING PigStorage(',');
B = FILTER A BY amount > 100;
C = GROUP B BY region;
D = FOREACH C GENERATE group, SUM(B.amount);
STORE D INTO 'result' USING PigStorage();

B. A = LOAD 'sales.txt' USING PigStorage(',');
B = FILTER A BY $2 > 100;
C = GROUP B BY $1;
D = FOREACH C GENERATE group, SUM(B.$2);
STORE D INTO 'result';

C. A = LOAD 'sales.txt' USING PigStorage(',');
B = FILTER A BY $2 > 100;
C = GROUP B BY $1;
D = FOREACH C GENERATE group, SUM(B.$2);
STORE D INTO 'result' USING PigStorage();

D. A = LOAD 'sales.txt' USING PigStorage(',');
B = FILTER A BY $1 > 100;
C = GROUP B BY $2;
D = FOREACH C GENERATE group, SUM(B.$3);
STORE D INTO 'result' USING PigStorage();

Solution

1. Step 1: Identify correct column indexes

   Columns: product_id ($0), region ($1), amount ($2). Filter by amount > 100 means FILTER BY $2 > 100.

2. Step 2: Group by region and sum amount

   Group by $1 (region), then sum B.$2 (amount) in FOREACH. STORE needs USING clause.

3. Step 3: Check each option

   A = LOAD 'sales.txt' USING PigStorage(','); B = FILTER A BY $2 > 100; C = GROUP B BY $1; D = FOREACH C GENERATE group, SUM(B.$2); STORE D INTO 'result' USING PigStorage(); matches all requirements: correct filter, group, sum, and STORE syntax.

4. Final Answer:

   Option C code sequence -> Option C

5. Quick Check:

   Filter $2>100, group $1, sum $2, STORE with USING [OK]

Hint: Use correct column indexes and STORE with USING [OK]

Common Mistakes:

• Using wrong column indexes for filter or group
• Omitting USING in STORE
• Summing wrong column