TY - GEN
T1 - Evaluation and analysis of capacity scheduler and fair scheduler in hadoop framework on big data technology
AU - Salman, Muhammad
AU - Husna, Diyanatul
AU - Wicaksono, Adhitya
AU - Ratna, Anak Agung Putri
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/11/23
Y1 - 2018/11/23
N2 - Apache Hadoop is an open source framework that implements MapReduce. It is scalable, reliable, and fault tolerant. Scheduling is an important process in Hadoop MapReduce. It is because scheduling has responsibility to allocate resources for running applications based on resource capacity, queues, running tasks, and the number of users. Changing single node to multi node Hadoop cluster can optimize HDFS, but quite costly. Scheduler performs the function of scheduling based on resource requirements, such as memory, CPU, disk, and network. The most general purpose of scheduling algorithm is minimizing the time of completing a task. Hadoop Scheduling is an independent module where users are able to design their own scheduler based on the application’s actual need. So it can fulfill the specific need of the business in accordance with the desired result. This research will analyze the characteristic of Capacity Scheduler and Fair Scheduler.
AB - Apache Hadoop is an open source framework that implements MapReduce. It is scalable, reliable, and fault tolerant. Scheduling is an important process in Hadoop MapReduce. It is because scheduling has responsibility to allocate resources for running applications based on resource capacity, queues, running tasks, and the number of users. Changing single node to multi node Hadoop cluster can optimize HDFS, but quite costly. Scheduler performs the function of scheduling based on resource requirements, such as memory, CPU, disk, and network. The most general purpose of scheduling algorithm is minimizing the time of completing a task. Hadoop Scheduling is an independent module where users are able to design their own scheduler based on the application’s actual need. So it can fulfill the specific need of the business in accordance with the desired result. This research will analyze the characteristic of Capacity Scheduler and Fair Scheduler.
KW - Big data
KW - Capacity scheduler
KW - Fair scheduler
KW - Hadoop
KW - YARN
UR - http://www.scopus.com/inward/record.url?scp=85062773085&partnerID=8YFLogxK
U2 - 10.1145/3293663.3293680
DO - 10.1145/3293663.3293680
M3 - Conference contribution
AN - SCOPUS:85062773085
T3 - ACM International Conference Proceeding Series
SP - 1
EP - 5
BT - AIVR 2018 - 2018 International Conference on Artificial Intelligence and Virtual Reality
PB - Association for Computing Machinery
T2 - 2018 International Conference on Artificial Intelligence and Virtual Reality, AIVR 2018
Y2 - 23 November 2018 through 25 November 2018
ER -