How to configure Replication Factor in HDFS?
hdfs-site.xml is used to configure HDFS. Changing the dfs.replication property in hdfs-site.xml will change the default replication for all files placed in HDFS.
You can also modify the replication factor on a per-file basis using the
Hadoop FS Shell:[training@localhost ~]$ hadoopfs –setrep –w 3 /my/fileConversely,
you can also change the replication factor of all the files under a directory.
[training@localhost ~]$ hadoopfs –setrep –w 3 -R /my/dir
How to compress mapper output but not the reducer output?
To achieve this compression, you should set:
conf.set("mapreduce.map.output.compress", true)
conf.set("mapreduce.output.fileoutputformat.compress", false)
What is the difference between Map Side join and Reduce Side Join?
Map side Join at map side is performed data reaches the map. You need a strict structure for defining map side join. On the other hand, Reduce side Join (Repartitioned Join) is simpler than map side join since the input datasets need not be structured. However, it is less efficient as it will have to go through sort and shuffle phases, coming with network overheads.
What is Hadoop streaming?
Hadoop distribution has a generic application programming interface for writing Map and Reduce jobs in any desired programming language like Python, Perl, Ruby, etc. This is referred to as Hadoop Streaming. Users can create and run jobs with any kind of shell scripts or executable as the Mapper or Reducers.
What are the limitations of importing RDBMS tables into Hcatalog directly?
There is an option to import RDBMS tables into Hcatalog directly by making use of –hcatalog –database option with the –hcatalog –table but the limitation to it is that there are several arguments like –as-avrofile , -direct, -as-sequencefile, -target-dir , -export-dir are not supported.
Is it sugggested to place the data transfer utility sqoop on an edge node ?
It is not suggested to place sqoop on an edge node or gateway node because the high data transfer volumes could risk the ability of hadoop services on the same node to communicate. Messages are the lifeblood of any hadoop service and high latency could result in the whole node being cut off from the hadoop cluster.
Explain about the core components of Flume.
The core components of Flume are –
Event- The single log entry or unit of data that is transported.
Source- This is the component through which data enters Flume workflows.
Sink-It is responsible for transporting data to the desired destination.
Channel- it is the duct between the Sink and Source.
Agent- Any JVM that runs Flume.
Client- The component that transmits event to the source that operates with the agent.
Does Flume provide 100% reliability to the data flow?
Yes, Apache Flume provides end to end reliability because of its transactional approach in data flow.
How can Flume be used with HBase?
Apache Flume can be used with HBase using one of the two HBase sinks –
HBaseSink (org.apache.flume.sink.hbase.HBaseSink) supports secure HBase clusters and also the novel HBase IPC that was introduced in the version HBase 0.96.
AsyncHBaseSink (org.apache.flume.sink.hbase.AsyncHBaseSink) has better performance than HBase sink as it can easily make non-blocking calls to HBase.
Working of the HBaseSink –
In HBaseSink, a Flume Event is converted into HBase Increments or Puts. Serializer implements the HBaseEventSerializer which is then instantiated when the sink starts. For every event, sink calls the initialize method in the serializer which then translates the Flume Event into HBase increments and puts to be sent to HBase cluster.
Working of the AsyncHBaseSink-
AsyncHBaseSink implements the AsyncHBaseEventSerializer. The initialize method is called only once by the sink when it starts. Sink invokes the setEvent method and then makes calls to the getIncrements and getActions methods just similar to HBase sink. When the sink stops, the cleanUp method is called by the serializer.
Explain about some important Sqoop commands other than import and export.
Create Job (--create)
Here we are creating a job with the name my job, which can import the table data from RDBMS table to HDFS. The following command is used to create a job that is importing data from the employee table in the db database to the HDFS file.
$ Sqoop job --create myjob \
--import \
--connect jdbc:mysql://localhost/db \
--username root \
--table employee --m 1
Verify Job (--list)
‘--list’ argument is used to verify the saved jobs. The following command is used to verify the list of saved Sqoop jobs.
$ Sqoop job --list
Inspect Job (--show)
‘--show’ argument is used to inspect or verify particular jobs and their details. The following command and sample output is used to verify a job called myjob.
$ Sqoop job --show myjob
Execute Job (--exec)
‘--exec’ option is used to execute a saved job. The following command is used to execute a saved job called myjob.
$ Sqoop job --exec myjob
How Sqoop can be used in a Java program?
The Sqoop jar in classpath should be included in the java code. After this the method Sqoop.runTool () method must be invoked. The necessary parameters should be created to Sqoop programmatically just like for command line.
What is the process to perform an incremental data load in Sqoop?
The process to perform incremental data load in Sqoop is to synchronize the modified or updated data (often referred as delta data) from RDBMS to Hadoop. The delta data can be facilitated through the incremental load command in Sqoop.
Incremental load can be performed by using Sqoop import command or by loading the data into hive without overwriting it. The different attributes that need to be specified during incremental load in Sqoop are-
1)Mode (incremental) –The mode defines how Sqoop will determine what the new rows are. The mode can have value as Append or Last Modified.
2)Col (Check-column) –This attribute specifies the column that should be examined to find out the rows to be imported.
3)Value (last-value) –This denotes the maximum value of the check column from the previous import operation.
Is it possible to do an incremental import using Sqoop?
Yes, Sqoop supports two types of incremental imports-
1)Append
2)Last Modified
To insert only rows Append should be used in import command and for inserting the rows and also updating Last-Modified should be used in the import command.
What is the standard location or path for Hadoop Sqoop scripts?
/usr/bin/Hadoop Sqoop
How can you check all the tables present in a single database using Sqoop?
The command to check the list of all tables present in a single database using Sqoop is as follows-
Sqoop list-tables –connect jdbc: mysql: //localhost/user;
How are large objects handled in Sqoop?
Sqoop provides the capability to store large sized data into a single field based on the type of data. Sqoop supports the ability to store-
1)CLOB ‘s – Character Large Objects
2)BLOB’s –Binary Large Objects
Large objects in Sqoop are handled by importing the large objects into a file referred as “LobFile” i.e. Large Object File. The LobFile has the ability to store records of huge size, thus each record in the LobFile is a large object.
Can free form SQL queries be used with Sqoop import command? If yes, then how can they be used?
Sqoop allows us to use free form SQL queries with the import command. The import command should be used with the –e and – query options to execute free form SQL queries. When using the –e and –query options with the import command the –target dir value must be specified.
Differentiate between Sqoop and distCP.
hdfs-site.xml is used to configure HDFS. Changing the dfs.replication property in hdfs-site.xml will change the default replication for all files placed in HDFS.
You can also modify the replication factor on a per-file basis using the
Hadoop FS Shell:[training@localhost ~]$ hadoopfs –setrep –w 3 /my/fileConversely,
you can also change the replication factor of all the files under a directory.
[training@localhost ~]$ hadoopfs –setrep –w 3 -R /my/dir
How to compress mapper output but not the reducer output?
To achieve this compression, you should set:
conf.set("mapreduce.map.output.compress", true)
conf.set("mapreduce.output.fileoutputformat.compress", false)
What is the difference between Map Side join and Reduce Side Join?
Map side Join at map side is performed data reaches the map. You need a strict structure for defining map side join. On the other hand, Reduce side Join (Repartitioned Join) is simpler than map side join since the input datasets need not be structured. However, it is less efficient as it will have to go through sort and shuffle phases, coming with network overheads.
Hadoop distribution has a generic application programming interface for writing Map and Reduce jobs in any desired programming language like Python, Perl, Ruby, etc. This is referred to as Hadoop Streaming. Users can create and run jobs with any kind of shell scripts or executable as the Mapper or Reducers.
There is an option to import RDBMS tables into Hcatalog directly by making use of –hcatalog –database option with the –hcatalog –table but the limitation to it is that there are several arguments like –as-avrofile , -direct, -as-sequencefile, -target-dir , -export-dir are not supported.
 |
| Fiserv Most Frequently Asked Latest Hadoop Interview Questions Answers |
Is it sugggested to place the data transfer utility sqoop on an edge node ?
It is not suggested to place sqoop on an edge node or gateway node because the high data transfer volumes could risk the ability of hadoop services on the same node to communicate. Messages are the lifeblood of any hadoop service and high latency could result in the whole node being cut off from the hadoop cluster.
Explain about the core components of Flume.
The core components of Flume are –
Event- The single log entry or unit of data that is transported.
Source- This is the component through which data enters Flume workflows.
Sink-It is responsible for transporting data to the desired destination.
Channel- it is the duct between the Sink and Source.
Agent- Any JVM that runs Flume.
Client- The component that transmits event to the source that operates with the agent.
Does Flume provide 100% reliability to the data flow?
Yes, Apache Flume provides end to end reliability because of its transactional approach in data flow.
How can Flume be used with HBase?
Apache Flume can be used with HBase using one of the two HBase sinks –
HBaseSink (org.apache.flume.sink.hbase.HBaseSink) supports secure HBase clusters and also the novel HBase IPC that was introduced in the version HBase 0.96.
AsyncHBaseSink (org.apache.flume.sink.hbase.AsyncHBaseSink) has better performance than HBase sink as it can easily make non-blocking calls to HBase.
Working of the HBaseSink –
In HBaseSink, a Flume Event is converted into HBase Increments or Puts. Serializer implements the HBaseEventSerializer which is then instantiated when the sink starts. For every event, sink calls the initialize method in the serializer which then translates the Flume Event into HBase increments and puts to be sent to HBase cluster.
Working of the AsyncHBaseSink-
AsyncHBaseSink implements the AsyncHBaseEventSerializer. The initialize method is called only once by the sink when it starts. Sink invokes the setEvent method and then makes calls to the getIncrements and getActions methods just similar to HBase sink. When the sink stops, the cleanUp method is called by the serializer.
Explain about some important Sqoop commands other than import and export.
Create Job (--create)
Here we are creating a job with the name my job, which can import the table data from RDBMS table to HDFS. The following command is used to create a job that is importing data from the employee table in the db database to the HDFS file.
$ Sqoop job --create myjob \
--import \
--connect jdbc:mysql://localhost/db \
--username root \
--table employee --m 1
Verify Job (--list)
‘--list’ argument is used to verify the saved jobs. The following command is used to verify the list of saved Sqoop jobs.
$ Sqoop job --list
Inspect Job (--show)
‘--show’ argument is used to inspect or verify particular jobs and their details. The following command and sample output is used to verify a job called myjob.
$ Sqoop job --show myjob
Execute Job (--exec)
‘--exec’ option is used to execute a saved job. The following command is used to execute a saved job called myjob.
$ Sqoop job --exec myjob
How Sqoop can be used in a Java program?
The Sqoop jar in classpath should be included in the java code. After this the method Sqoop.runTool () method must be invoked. The necessary parameters should be created to Sqoop programmatically just like for command line.
What is the process to perform an incremental data load in Sqoop?
The process to perform incremental data load in Sqoop is to synchronize the modified or updated data (often referred as delta data) from RDBMS to Hadoop. The delta data can be facilitated through the incremental load command in Sqoop.
Incremental load can be performed by using Sqoop import command or by loading the data into hive without overwriting it. The different attributes that need to be specified during incremental load in Sqoop are-
1)Mode (incremental) –The mode defines how Sqoop will determine what the new rows are. The mode can have value as Append or Last Modified.
2)Col (Check-column) –This attribute specifies the column that should be examined to find out the rows to be imported.
3)Value (last-value) –This denotes the maximum value of the check column from the previous import operation.
Is it possible to do an incremental import using Sqoop?
Yes, Sqoop supports two types of incremental imports-
1)Append
2)Last Modified
To insert only rows Append should be used in import command and for inserting the rows and also updating Last-Modified should be used in the import command.
What is the standard location or path for Hadoop Sqoop scripts?
/usr/bin/Hadoop Sqoop
How can you check all the tables present in a single database using Sqoop?
The command to check the list of all tables present in a single database using Sqoop is as follows-
Sqoop list-tables –connect jdbc: mysql: //localhost/user;
How are large objects handled in Sqoop?
Sqoop provides the capability to store large sized data into a single field based on the type of data. Sqoop supports the ability to store-
1)CLOB ‘s – Character Large Objects
2)BLOB’s –Binary Large Objects
Large objects in Sqoop are handled by importing the large objects into a file referred as “LobFile” i.e. Large Object File. The LobFile has the ability to store records of huge size, thus each record in the LobFile is a large object.
Can free form SQL queries be used with Sqoop import command? If yes, then how can they be used?
Sqoop allows us to use free form SQL queries with the import command. The import command should be used with the –e and – query options to execute free form SQL queries. When using the –e and –query options with the import command the –target dir value must be specified.
Differentiate between Sqoop and distCP.
DistCP utility can be used to transfer data between clusters whereas Sqoop can be used to transfer data only between Hadoop and RDBMS.
Post a Comment