Advanced Analytics—Technology and Tools: MapReduce and Hadoop - Data Science and Big Data Analytics - page 427

processed. Prior to the STORE command, Pig had begun to build an execution plan
but had not yet initiated MapReduce processing.

Pig provides for the execution of several common data manipulations, such as
inner and outer joins between two or more files (tables), as would be expected
in a typical relational database. Writing these joins explicitly in MapReduce using
Hadoop would be quite involved and complex. Pig also provides a GROUP BY
functionality that is similar to the Group By functionality offered in SQL. Chapter
11 has more details on using Group By and other SQL statements.
An additional feature of Pig is that it provides many built-in functions that are
easily utilized in Pig code. Table 10.1 includes several useful functions by category.

Table 10.1 Built-In Pig Functions

Eval Load/Store Math String DateTime

AVG BinStorage() ABS INDEXOF AddDuration

CONCAT JsonLoader CEIL LAST_INDEX_OF CurrentTime

COUNT JsonStorage COS,

ACOS

LCFORST DaysBetween

COUNT_STAR PigDump EXP LOWER GetDay

DIFF PigStorage FLOOR REGEX_EXTRACT GetHour

IsEmpty TextLoader LOG,

LOG10

REPLACE GetMinute

MAX HBaseStorage RANDOM STRSPLIT GetMonth

MIN ROUND SUBSTRING GetWeek

SIZE SIN,

ASIN

TRIM GetWeekYear

SUM SQRT UCFIRST GetYear

TOKENIZE TAN,

ATAN

UPPER MinutesBetween

SubtractDuration
ToDate