Will pig show any warning if there is no matching field?
No, Pig will not show any warning if there is no matching field or a mismatch. If you assume that Pig gives such a warning, then it is difficult to find in log file. If any mismatch is found, it assumes a null value in Pig.
Can a pig script have multiple describes?
A pig script can have multiple describes. 35. Is it possible to join multiple fields in pig scripts? Yes, Join select records from one input and join with another input.This is done by indicating keys for each input. When those keys are equal, the two rows are joined.
Why do we use pig instead of MapReduce?
It is because Pig Latin is SQL-like language. In order to support data operations, it offers many built-in operators like joins, filters, ordering, and many more. And, it offers nested data types that are missing from MapReduce, for example, tuples, bags, and maps. Que 3. What is the difference between Pig and SQL? Ans.
Is it possible to join multiple fields in pig scripts?
Yes, it is possible to join multiple fields in PIG scripts because the join operations takes records from one input and joins them with another input. This can be achieved by specifying the keys for each input and the two rows will be joined when the keys are equal.
Which of the following is not true in Pig?
Which of the following is not true about Pig? B. Pig can not perform all the data manipulation operations in Hadoop.
Which of the following definitions of complex data types in Pig are correct?
Which of the following definitions of complex data types in Pig are correct? Tuple: a set of key/value pairs.
What is Pig Latin mention its significances in handling large data?
Pig Latin is a dataflow language. Each processing step results in a new data set, or relation. In input = load 'data' , input is the name of the relation that results from loading the data set data. A relation name is referred to as an alias. Relation names look like variables, but they are not.
Does Pig support processing data in pipeline?
Yes, pig supports both single line and multi-line commands. In single line command it executes the data, but it doesn't store in the file system, but in multiple lines commands it stores the data into '/output';/* , so it can store the data in HDFS.
What is the default data type of fields in Pig?
byte arrayDefault datatype is byte array in pig if type is not assigned. If schema is given in load statement, load function will apply schema and if data and datatype is different than loader will load Null values or generate error.
What is the primary purpose of Pig?
A) Pig is a high-level scripting language that is used with Apache Hadoop. Pig enables data workers to write complex data transformations without knowing Java.
Why Pig is used in big data?
Pig Represents Big Data as data flows. Pig is a high-level platform or tool which is used to process the large datasets. It provides a high-level of abstraction for processing over the MapReduce. It provides a high-level scripting language, known as Pig Latin which is used to develop the data analysis codes.
What is the difference between Hive and Pig?
1) Hive Hadoop Component is used mainly by data analysts whereas Pig Hadoop Component is generally used by Researchers and Programmers. 2) Hive Hadoop Component is used for completely structured Data whereas Pig Hadoop Component is used for semi structured data.
How can you use Pig for ETL processing?
A good example of a Pig application is the ETL transaction model that describes how a process will extract data from a source, transform it according to a rule set and then load it into a datastore. Pig can ingest data from files, streams or other sources using the User Defined Functions(UDF).
Is Pig an ETL tool?
Pig can be used to run ETL jobs on Hadoop. It saves you from writing MapReduce code in Java while its syntax may look familiar to SQL users.
Why Pig is called data flow language?
Pig Latin is a data flow language. This means it allows users to describe how data from one or more inputs should be read, processed, and then stored to one or more outputs in parallel.
What is the difference between Pig and SQL?
Pig Latin is a procedural language. SQL is a declarative language. In Apache Pig, schema is optional. We can store data without designing a schema (values are stored as $01, $02 etc.)
Which among the following is a complex data type supported by Pig Latin?
What are the data types of Pig Latin? Pig Latin can handle both atomic data types like int, float, long, double etc. and complex data types like tuple, bag and map.
What are complex data types in hive?
Hive complex data types such as arrays, maps, and structs are a composite of primitive or complex data types. Informatica Developer represents complex data types with the string data type and uses delimiters to separate the elements of the complex data type.
Which of the following function is used to read data in Pig?
Which of the following function is used to read data in PIG? Explanation: PigStorage is the default load function. 7.
Which of the following is an example for tuple data type in Pig?
Tuple : An ordered set of fields. Tuple is represented by braces. Example: (1,2) Bag : A set of tuples is called a bag.
Saturday, 7 September 2013
Can you give us some examples how Hadoop is used in real time environment?
Pig Interview Questions
Can you give us some examples how Hadoop is used in real time environment?
What is pig analysis?
Pig is a platform to analyze large data sets that should either structured or unstructured data by using Pig latin scripting. Intentionally done for streaming data, un-structured data in parallel
Why are macros introduced in Pig?
Macros are introduced in the later versions of pig. The main intention in introducing macros is to make the pig language modular. Generally in other languages, we create a function to use to multiple times similarly in pig we can create a macro in pig and we can run the macro number of times.
What is Apache Pig?
To analyze large data sets representing them as data flows, we use Apache Pig. Basically, to provide an abstraction over MapReduce, reducing the complexities of writing a MapReduce task using Java programming, Apache Pig is designed. Moreover, using Apache Pig, we can perform data manipulation operations very easily in Hadoop.
What are some examples of operations in Pig?
In order to perform several operations, Pig offers many operators, for example, join, sort, filer and many more.
What is the most common usecase for pig?
Most common usecase for pig is data pipeline.
Can a pig script run on Kerberos?
As a consequence of running a pig script on a Kerberos secured Hadoop cluster limits the running time to at most the remaining validity time of these Kerberos tickets. When doing really complex analytics this may become a problem as the job may need to run for a longer time than these ticket times allow.
Can you override exec in Pig?
We have to override the method exec () while writing UDF in the Pig. Whereas the base class can be different while writing filter UDF, we will have to extend FilterFunc and for evaluate UDF, we will have to extend the EvalFunc. EvaluFunc is parameterized and must provide the return type also.
Relational operators
UNION combines multiple relations together whereas SPLIT partitions a relation into multiple ones. An example will make it clear:
Parallelism
each job. You do this using a PARALLEL clause for operators that run in the reduce
Parameter Substitution
to be able to run the same script with different parameters. For example, a script that