The reduce phase of the mapreduce job takes this intermediate data as input, and applies another programmer. The term speculative execution has been used in different contexts. Speculative execution can be turned off by setting these properties to false mapred. In hadoop implementation, each slave node has 2 map slots and 2 reduce slots by default. Several speculative execution strategies have been proposed in the literature for the mapreduce system and its variants or derivatives. May 16, 2019 the reason its speculative execution, of course, is because the cpu might be wrong.
A mechanism called speculative execution is embedded into hadoop to mitigate slow tasks. So, for example, below speculative execution for maps set to off but is on for reducers. You can disable speculative execution for the mappers and reducers by setting the mapred. It has been shown that speculative execution can decrease the job execution time by 44% 10. Another way of setting it runtime that makes experimentingtesting easier is by passing corresponding arguments in the command line. For a map, the progress score is the fraction of input data read. Optimization for speculative execution of multiple jobs in a. Therefore, the accuracy and efficiency for computing are needed to be assured and speculative execution is an efficient method for calculation of fault tolerance. Our simulation results show both sca and sda can reduce the job.
Speculative execution in hadoop framework is an optimization technique to ensure that the submitted job finishes in a timebound manner. If it is, the system loads the appropriate data and executes those instructions instead. The concept behind speculative execution is that instructions are executed ahead of knowing that they are required. The speculative execution is used to offset the impact of the slow workers in the cluster. Theoutput of the map phase is a list of keys and their associated value lists. Speculative execution an overview sciencedirect topics. Preventing speculative execution attacks at their source. If a task of a job requires an abnormally long execution time, then the total completion time of the job is affected. In hadoop, speculative execution is a process that takes place during the slower execution of a task at a node. Request pdf a survey of speculative execution strategy in mapreduce mapreduce is a parallel computing programming model designed to process. Speculative execution mapreducespark stack overflow. So, this paper uses late7 which defines a task is straggling or not. To take a more systematic approach for the design of speculative execution strategies, our previous work e.
Nov 14, 2018 you need to set the configuration parameters mapreduce. Job execution time depends on the slowest map and reduce tasks. How can i turn off hadoop speculative execution from java. Efficient checkpoint interval for speculative execution in. This will reduce the job execution time if the task progress is slow due to memory unavailability. Mapreduce hadoop implementation for the distributed execution environment and bigtable hbase imple mentation as the distributed storage infrastructure.
Improving mapreduce performance with partial speculative. A task slot gets occupied when a task is assigned to it, and gets released when the task completes. Thefactthat victim and attacker are in different processes complicates matters, as the context of the execution i. A detailed study of the performance and power cost of speculative execution in hadoop. Mapreduce is a parallel computing programming model designed to process largescale data. Transactional support in mapreduce for speculative parallelism. Jul 26, 2015 hadoop uses this speculative execution to mitigate the slowtask problem. When a node has an empty task slot, hadoop chooses a task for it from one of three categories. Hadoop supports speculative execution to cope with the situations where some tasks in a job become laggard compared with other tasks. Predicting execution bottlenecks in mapreduce clusters usenix.
Since the speculative task and the original task both are working on the same set of data, output of which ever task finishes first successfully is used and the other one is killed. Nov 14, 2018 the main work of speculative execution is to reduce the job execution time. When a mapreduce job is submitted there will be several map tasks running in parallel working on the portion of the data input splits. Speculative execution for a single job in a mapreducelike. Index termsjob scheduling, speculative execution, cloning, straggler. Optimized speculative execution to improve performance of mapreduce jobs on virtualized computing environment. Improving resource utilization in mapreduce digital science center.
Aug 02, 2016 lets keep aside speculative execution for some time. They begin speculative execution only when the map or the reduce. Optimization, not a feature to make jobs run more reliably. May 23, 2015 it is the option for hadoop to specify backup tasks if it detects that there are some slow tasks on a few of the cluster nodes. Work is done before it is known whether it is actually needed, so as to prevent a delay that would have to be incurred by doing the work after it is known that it is needed. Sep 29, 2015 speculative execution is proposed to mitigate stragglers. Improving mapreduce performance with progress and feedback. Transactional support in mapreduce for speculative parall elism.
On understanding the energy impact of speculative execution. Hadoop is a widely used opensource implementation of. This is done so that any slow running task doesnt slow down the whole job. Since in speculative execution redundant tasks are being executed, thus this can reduce overall throughput. Improving mapreduce performance using smart speculative. Pdf optimization for speculative execution in big data.
Theinput for mapreduce is a list of key 1, value 1 pairs and map is applied to each pair to compute intermediate keyvalue pairs, key 2, value 2. In this process, the master node starts executing another instance of that same task on the other node. Intel analysis of speculative execution side channels. Recently, virtualization has become more and more important in the cloud computing to support efficient flexible resource provisioning. The mapreduce model consists of two primitive functions. Hadoop speculative execution not data science medium. When forcing a mapper to take significantly longer than other map tasks, speculative map tasks are launched even if the mapreduce. The assumption of speculative execution is that the execution time of map tasks does not differ much, which makes it possible for hadoop to predict map task execution time without any prior knowledge. Same way several reduce tasks will be spawned to work in parallel to produce the final output.
Whenever it is seen that a task is running slow, the hadoop platform will schedule redundant copies of that task across several nodes which do not have other work to perform. For the heavily loaded case, we propose the enhanced speculative execution ese algorithm which is an extension of the microsoft mantri scheme. However, the performance interference among virtual machines may affect the efficiency of the resource provisioning. What happens when speculative execution is off for both map. Optimized speculative execution to improve performance of.
Speculative execution in hadoop mapreduce is an optimization where slow running map or reduce tasks are started on another node too. If speculative execution is enabled, the job tracker will issue multiple instances of the same task on multiple nodes and it will take the result of the task that finished first. Hadoop speculative task execution intellipaat community. For a reduce task, the execution is divided into three phases, each of which accounts for of the score. After that, based on expected job completion time, the formulated. Speculative execution in hadoop speculative execution in hadoop mapreduce is an option to run a duplicate map or reduce task for the same input data on an alternative node. Speculative execution in hadoop mapreduce dataflair. A survey of speculative execution strategy in mapreduce. Speculative execution if hadoop detects that some task is slower than normal, another equivalent backup task is launched. Speculative execution is an efficient method of processing straggling tasks by monitoring the realtime rate of running tasks and backing up straggler on another node to increase the. The mapreduce model is to break jobs into tasks and run the tasks in parallel to make the overall job execution time smaller than it would be if the tasks ran sequentially. Speculative execution backup tasks solving problems. For example, although the conventional join algorithm in mapreduce requires both map and reduce phases, if the data are sorted on the join attribute, the join can be implemented directly in. Our use of a functional model with userspecied map and reduce operations allows us to parallelize large computations easily and to use reexecution as the primary mechanism for fault tolerance.
The backup tasks will be preferentially scheduled on the faster nodes. Google simply backs up the last few running map or reduce tasks and has observed that speculative execution can decrease the job execution time by 44% 1. Request pdf speculative execution for a single job in a mapreducelike system parallel processing plays an important role for largescale data analytics. Improving mapreduce performance in heterogeneous environments. Which ever completes first, the second one is killed immediately. To select speculative tasks, hadoop monitors task progress using a progress score between 0 and 1. And the task which is finished first is accepted and the execution of other is stopped by killing that. In this paper, we explore an approach to increase the efficiency of speculative execution, and further improve mapreduce performance. You can disable speculative execution for mappers and reducers in mapredsite. The hard partition of physical processing capability into virtual map. What is speculative execution in mapreduce archives. A tradeoff between execution overhead and parallelism 25 rule of thumb.
Mapreduce2062 speculative execution is too aggressive. Speculative execution is an optimization technique where a computer system performs some task that may not be needed. Experiments show that there are always some map or reduce tasks that execute much more slowly than others, therefore increasing the execution time of the whole job. Now, in general, whenever a task fails and tasktracker identifies it then the jobtracker schedules that task on a different slave and waits for its successful completion. Ieee transactions on computers 1 improving mapreduce. Speculative execution for a single job in a mapreducelike system. Intel analysis of speculative execution side channels download pdf white paper. Observations on factors affecting performance of mapreduce. However, the existing speculative execution mechanism could not work efficiently as many speculative tasks are still slower than their original tasks. Map tasks and reduce tasks can be executed in parallel because the data of these two types of tasks are independent.