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What does SerDe in the Hive mean?
Serializer or Deserializer is the full form of SerDe. Hive's SerDe feature lets you read data from a table and write data in any format you like for a particular field.
Serializer or Deserializer is the full form of SerDe. Hive’s SerDe feature lets you read data from a table and write data in any format you like for a particular field.
See lessWhat role does Apache Hadoop’s distributed cache play?
Distributed cache, a key utility feature of Hadoop, enhances job performance by caching the files used by applications. Using JobConf settings, an application can specify a file for the cache. The Hadoop framework copies these files to each node where a task must be run. This is carried out prior toRead more
Distributed cache, a key utility feature of Hadoop, enhances job performance by caching the files used by applications. Using JobConf settings, an application can specify a file for the cache.
The Hadoop framework copies these files to each node where a task must be run. This is carried out prior to the task’s execution. In addition to zip and jar files, Distributed Cache offers the dissemination of read-only files.
See lessDescribe the HDFS Safe mode.
In a cluster, NameNode operates in read-only mode, while NameNode starts out in Safe Mode. Safe Mode inhibits writing to the file system. At this point, it gathers information and statistics from each DataNode.
In a cluster, NameNode operates in read-only mode, while NameNode starts out in Safe Mode. Safe Mode inhibits writing to the file system. At this point, it gathers information and statistics from each DataNode.
See lessDefine Balancer in HDFS.
The balancer in HDFS is a tool the admin staff leverages to shift blocks from overused to underused nodes and redistribute data across DataNodes.
The balancer in HDFS is a tool the admin staff leverages to shift blocks from overused to underused nodes and redistribute data across DataNodes.
See lessWhat is Hadoop’s “Data Locality?”
Data movement over the network is unnecessary in a Big Data system due to the amount of data. Hadoop is now attempting to bring processing closer to the data. The information is kept local to the storage place in this manner.
Data movement over the network is unnecessary in a Big Data system due to the amount of data. Hadoop is now attempting to bring processing closer to the data. The information is kept local to the storage place in this manner.
See lessWhy does Hadoop employ the context object?
The Hadoop framework uses context objects with the Mapper class to communicate with the rest of the system. The system configuration information and job are passed to the context object in its function Object() { [native code] }. To pass information in the setup(), cleanup(), and map() functions, weRead more
The Hadoop framework uses context objects with the Mapper class to communicate with the rest of the system. The system configuration information and job are passed to the context object in its function Object() { [native code] }.
To pass information in the setup(), cleanup(), and map() functions, we employ context objects. With the help of this object, crucial data is made available for map operations.
See lessWhat occurs if a user submits a new job when NameNode is down?
Hadoop's NameNode is a single point of failure, making it impossible for users to submit or run new jobs. The user must wait for NameNode to restart before performing any jobs since if NameNode is down, the job may fail.
Hadoop’s NameNode is a single point of failure, making it impossible for users to submit or run new jobs. The user must wait for NameNode to restart before performing any jobs since if NameNode is down, the job may fail.
See lessWhat are the Secondary NameNode’s functions?
Secondary NameNode's functions are as follows: FsImage, which keeps a copy of both the FsImage and EditLog files. NameNode failure: The Secondary NameNode's FsImage can be used to reconstruct the NameNode if it crashes. Checkpoint: Secondary NameNode uses this checkpoint to ensure that HDFS data isRead more
Secondary NameNode’s functions are as follows:
- FsImage, which keeps a copy of both the FsImage and EditLog files.
- NameNode failure: The Secondary NameNode’s FsImage can be used to reconstruct the NameNode if it crashes.
- Checkpoint: Secondary NameNode uses this checkpoint to ensure that HDFS data is not damaged.
- Update: The EditLog and FsImage files are both automatically updated. Updating the FsImage file on the Secondary NameNode is beneficial.
See lessExplain “rack awareness.”
When reading or writing any file located closer to the neighboring rack to the Read or Write request in the Hadoop cluster, Namenode leverages the Datanode to reduce network traffic. Namenode keeps track of each DataNode's rack id, which is known as rack awareness.
When reading or writing any file located closer to the neighboring rack to the Read or Write request in the Hadoop cluster, Namenode leverages the Datanode to reduce network traffic.
Namenode keeps track of each DataNode’s rack id, which is known as rack awareness.
See lessHow do you turn off the HDFS Data Node’s Block Scanner?
Set dfs.datanode.scan.period.hours to 0 to disable Block Scanner on HDFS Data Node.
Set dfs.datanode.scan.period.hours to 0 to disable Block Scanner on HDFS Data Node.
See less