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Posted to commits@wayang.apache.org by be...@apache.org on 2021/03/30 21:34:16 UTC
[incubator-wayang-website] 03/06: add paper socc 19
This is an automated email from the ASF dual-hosted git repository.
bertty pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/incubator-wayang-website.git
commit e4695f2c26e9560e0609e99c992edd8bb628b4bb
Author: Bertty Contreras-Rojas <be...@scalytics.io>
AuthorDate: Tue Mar 30 18:20:53 2021 -0300
add paper socc 19
Signed-off-by: Bertty Contreras-Rojas <be...@scalytics.io>
---
_publications/2019-11-20-socc.md | 31 +++++++++++++++++++++++++++++++
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+---
+license: |
+ Licensed to the Apache Software Foundation (ASF) under one or more
+ contributor license agreements. See the NOTICE file distributed with
+ this work for additional information regarding copyright ownership.
+ The ASF licenses this file to You under the Apache License, Version 2.0
+ (the "License"); you may not use this file except in compliance with
+ the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+layout: publication
+title: Publication
+subtitle: >
+ TagSniff: Simplified Big Data Debugging for Dataflow Jobs
+link-name: ICDE 2019
+img-thumb: assets/img/screenshot/rheem.png
+authors: Bertty Contreras-Rojas, Jorge-Arnulfo Quiané-Ruiz, Zoi Kaoudi, Saravanan Thirumuruganathan
+year: 2019
+month: 11
+day: 20
+link-paper: assets/pdf/paper/socc19.pdf
+link-external: false
+---
+
+Although big data processing has become dramatically easier over the last decade, there has not been matching progress over bigdata debugging. It is estimated that users spend more than 50% of their time debugging their big data applications, wasting machine resources and taking longer to reach valuable insights. One cannot simply transplant traditional debugging techniques to big data. In this paper, we propose the TagSniff model, which can dramatically simplify data debugging for dataf [...]
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