{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T07:05:04Z","timestamp":1761807904431},"reference-count":16,"publisher":"Association for Computing Machinery (ACM)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2012,2]]},"abstract":"<jats:p>\n            Analyzing large scale data has emerged as an important activity for many organizations in the past few years. This large scale data analysis is facilitated by the MapReduce programming and execution model and its implementations, most notably Hadoop. Users of MapReduce often have analysis tasks that are too complex to express as individual MapReduce jobs. Instead, they use high-level query languages such as Pig, Hive, or Jaql to express their complex tasks. The compilers of these languages translate queries into workflows of MapReduce jobs. Each job in these workflows reads its input from the distributed file system used by the MapReduce system and produces output that is stored in this distributed file system and read as input by the next job in the workflow. The current practice is to delete these intermediate results from the distributed file system at the end of executing the workflow. One way to improve the performance of workflows of MapReduce jobs is to keep these intermediate results and reuse them for future workflows submitted to the system. In this paper, we present\n            <jats:italic>ReStore<\/jats:italic>\n            , a system that manages the storage and reuse of such intermediate results. ReStore can reuse the output of whole MapReduce jobs that are part of a workflow, and it can also create additional reuse opportunities by materializing and storing the output of query execution operators that are executed within a MapReduce job. We have implemented ReStore as an extension to the Pig dataflow system on top of Hadoop, and we experimentally demonstrate significant speedups on queries from the PigMix benchmark.\n          <\/jats:p>","DOI":"10.14778\/2168651.2168659","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"586-597","source":"Crossref","is-referenced-by-count":75,"title":["ReStore"],"prefix":"10.14778","volume":"5","author":[{"given":"Iman","family":"Elghandour","sequence":"first","affiliation":[{"name":"University of Waterloo"}]},{"given":"Ashraf","family":"Aboulnaga","sequence":"additional","affiliation":[{"name":"University of Waterloo"}]}],"member":"320","published-online":{"date-parts":[[2012,2]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Apache Hadoop. Available at: http:\/\/hadoop.apache.org\/.  Apache Hadoop. Available at: http:\/\/hadoop.apache.org\/."},{"key":"e_1_2_1_2_1","unstructured":"Apache Pig. Available at: http:\/\/pig.apache.org\/.  Apache Pig. Available at: http:\/\/pig.apache.org\/."},{"key":"e_1_2_1_3_1","unstructured":"Hadoop Distributed File System. Available at: http:\/\/hadoop.apache.org\/hdfs\/.  Hadoop Distributed File System. Available at: http:\/\/hadoop.apache.org\/hdfs\/."},{"key":"e_1_2_1_4_1","unstructured":"PigMix. Available at: https:\/\/cwiki.apache.org\/confluence\/display\/PIG\/PigMix.  PigMix. Available at: https:\/\/cwiki.apache.org\/confluence\/display\/PIG\/PigMix."},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.14778\/1453856.1453960"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/1066157.1066292"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1559845.1559935"},{"key":"e_1_2_1_8_1","volume-title":"Proc. VLDB Endow. (PVLDB), 4(12)","author":"Beyer K. S.","year":"2011","unstructured":"K. S. Beyer : A scripting language for large scale semistructured data analysis . Proc. VLDB Endow. (PVLDB), 4(12) :1272--1283, 2011 . K. S. Beyer et al. Jaql: A scripting language for large scale semistructured data analysis. Proc. VLDB Endow. (PVLDB), 4(12):1272--1283, 2011."},{"key":"e_1_2_1_9_1","first-page":"137","volume-title":"Proc. OSDI","author":"Dean J.","year":"2004","unstructured":"J. Dean and S. Ghemawat . MapReduce: Simplified data processing on large clusters . In Proc. OSDI , pages 137 -- 150 , 2004 . J. Dean and S. Ghemawat. MapReduce: Simplified data processing on large clusters. In Proc. OSDI, pages 137--150, 2004."},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2213836.2213937"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687553.1687568"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/s007780100054"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.14778\/1920841.1920906"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/1376616.1376726"},{"key":"e_1_2_1_15_1","volume-title":"Proc. VLDB Endow. (PVLDB), 2(2):1626--1629","author":"Thusoo A.","year":"2009","unstructured":"A. Thusoo : a warehousing solution over a Map-Reduce framework . Proc. VLDB Endow. (PVLDB), 2(2):1626--1629 , 2009 . A. Thusoo et al. Hive: a warehousing solution over a Map-Reduce framework. Proc. VLDB Endow. (PVLDB), 2(2):1626--1629, 2009."},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/1807167.1807278"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/2168651.2168659","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T09:18:35Z","timestamp":1672219115000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/2168651.2168659"}},"subtitle":["reusing results of MapReduce jobs"],"short-title":[],"issued":{"date-parts":[[2012,2]]},"references-count":16,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2012,2]]}},"alternative-id":["10.14778\/2168651.2168659"],"URL":"https:\/\/doi.org\/10.14778\/2168651.2168659","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2012,2]]}}}