A Pig Latin is made of a series of operations, or transformations, that are applied to the input data to produce output.
Under the cover pig turns the transformations
into a series of MapReduce jobs, but as a programmer you are mostly
unaware of this, which allows you to focus on the data rather than the
nature of the execution.
Pig runs in 2 modes :
1) Local Mode
2) Hadoop Mode
1) Local Mode : In
local mode Pig runs in a single JVM & accesses the local file
system. This mode is suitable only for small datasets & when trying
out Pig. Local mode doesn't use Hadoop. Also it doesn't use Hadoop's
local job runner, instead Pig translates queries into a physical plan
that it executes itself. The execution type is set using the -x or
-exectype option. To run in local mode, set the option to local:
$ pig -x local
2) Hadoop Mode : In
Hadoop mode, Pig translates queries into MapReduce jobs & runs them
on a Hadoop cluster. To use Hadoop mode you need to tell Pig which
vesion of Hadoop you are using & where your cluster is running.
The Environment variable PIG_HADOOP_VERSION is used to tell Pig the version of Hadoop it is connecting to.
$ export PIG_HADOOP_VERSION = 20
Next we need to point Pig at the cluster namenode
& jobtracker. If you already have Hadoop site file that define
fs.default.name & mapred.jobtracker you can simply add Hadoop's
configuration directory to Pig's classpath :
$ export PIG_CLASSPATH = $HADOOP_INSTALL/conf/
Alternatively ou can create a pig.properties file in Pig's “conf” directory, which sets these two properties. Here is an example for a pseudo-distributed setup :
once you have configured Pig to connect to a Hadoop
cluster, you can launch Pig, setting the -x option to MapReduce or
omitting it entirely, as Hadoop mode is the default:
PIG_PATH = $HADOOP_HOME/bin/pig-0.7.0
PIG_CLASSPATH = $PIG_PATH/pig-0.3.0-core.jar:$HADOOP_HOME/conf \ PIG_HADOOP_VERSION = 0.20.2 \ $PIG_PATH/bin/pig $@