1.
1) Memory Tuning.2.
2) Improving IO Performance.3.
3) Minimizing the Disk Spill by Compressing Map Output.4.
4) Tuning the Number of Mapper or Reducer Tasks.5.
5) Writing a Combiner.6.
6) Using Skewed Joins.7.
7) Speculative Execution..
Hadoop clusters are easily scalable and can quickly add nodes to increase throughput, and maintain processing speed, when faced with increasing data blocks.
The use of low cost, high availability commodity hardware makes Hadoop clusters relatively easy and inexpensive to set up and maintain..
The benchmark measures the number of operations performed by the name-node per second.
Specifically, for each operation tested, it reports the total running time in seconds (Elapsed Time), operation throughput (Ops per sec), and average time for the operations (Average Time).
The higher, the better..
TeraSort benchmark measures the time to sort 1 TB of randomly generated data..
TeraValidate: Validate the sorted output data of TeraSort
A map task ensures that each key is less than or equal to the previous one.Apr 9, 2011.
DFSIO is a benchmark test that comes with Hadoop, which can be used to analyze the I/O performance of an HDFS cluster.
This recipe shows how to use DFSIO to benchmark the read/write performance of an HDFS cluster..
In the last couple of years, many proposals came from different research groups about the suitability of Hadoop and Spark frameworks when various types of data of different sizes are used as input in different clusters.
Therefore, it becomes necessary to study the performance of the frameworks and understand the influence of various parameters.
Let me first talk about a few things that you should be aware of while reading through this article.
MRBench (see src/test/org/apache/hadoop/mapred/MRBench.java) loops a small job a number of times.
As such it is a very complimentary benchmark to the “large-scale” TeraSort benchmark suite because MRBench checks whether smalljob runs are responsive and running efficiently on your cluster.
It puts its focus on the MapReduce layer as its impact on th.
NNBench (see src/test/org/apache/hadoop/hdfs/NNBench.java) is useful for load testing the NameNode hardware and configuration.
It generates a lot of HDFS-related requests with normally very small “payloads” for the sole purpose of putting a high HDFS management stress on the NameNode.
The benchmark can simulate requests for creating, reading, renam.
The Hadoop distribution comes with a number of benchmarks, which are bundled in hadoop-*test*.jar and hadoop-*examples*.jar.
The four benchmarks we will be looking at in more details are TestDFSIO, nnbench, mrbench (in hadoop-*test*.jar) and TeraGen / TeraSort / TeraValidate (in hadoop-*examples*.jar).
Here is the full list of available options in .
I hope you have found my quick overview of Hadoop’s benchmarking and testing tools useful! Feel free to provide your feedback, corrections and suggestions in the comments below.
The TeraSort benchmark is probably the most well-known Hadoop benchmark.
Back in 2008, Yahoo! set a record by sorting 1 TB of data in 209 seconds – on an Hadoop cluster of 910 nodes as Owen O’Malley of the Yahoo! Grid Computing Team reports.
One year later in 2009, Yahoo! set another record by sorting a 1 PB (1’000 TB) of data in 16 hourson an even.
The TestDFSIO benchmark is a read and write test for HDFS.
It is helpful for tasks such as stress testing HDFS, to discover performance bottlenecks in your network, to shake out the hardware, OS and Hadoop setup of your cluster machines (particularly the NameNode and the DataNodes) and to give you a first impression of how fast your cluster is in t.
This page is to discuss benchmarking Hadoop using tools it provides.
NNThroughputBenchmark, as its name indicates, is a name-node throughput benchmark, which runs a series of client threads on a single node against a name-node.
Hadoop clusters can deliver the most optimal performance when the load on cluster is evenly distributed across all the nodes.
This enables the processing tasks to run without being constrained by RAM, CPU, or disk resources on individual nodes.
In this article I introduce some of the benchmarking and testing tools that are included in the Apache Hadoop distribution.
Namely, we look at the benchmarks TestDFSIO, TeraSort, NNBench and MRBench.
These are popular choices to benchmark and stress test an Hadoop cluster.
Specific model for organizing a set of computers
Specific model for organizing a set of computers
