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update and resolve conflict
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.gitignore

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ddf-runtime
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.*.swp
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.cache
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### Maven
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# These files should be generated by, e.g., bin/make-poms.sh
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spark_adatao/pom.xml
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pa/pom.xml
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contrib/pom.xml
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### Eclipse
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# These files should be generated by, e.g., bin/make-*-eclipse.sh
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.project
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.classpath
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.settings
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### R
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# History files
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.Rhistory
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# Example code in package build process
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*-Ex.R
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### Java
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*.class
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# Mobile Tools for Java (J2ME)
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.mtj.tmp/
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# Package Files #
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#*.jar
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#*.war
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#*.ear
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### Scala
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*.class
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*.swp
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*.log
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# sbt specific
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.cache/
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.history/
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.lib/
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dist/*
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target/
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.idea
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.idea_modules
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.DS_Store
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.part-00000.crc
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.cache
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.settings/
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metastore_db/
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wordcount-input.txt
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# The project pom.xml's are generated by "bin/make-poms.sh"
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*/pom.xml
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# The root pom.xml is manually maintained
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!./pom.xml
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# Eclipse .classpath and .project are generated by "bin/make-eclipse-projects.sh"
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*/.classpath
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*/.project
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# lib_managed/ is generated by "sbt compile"
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lib_managed/
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src_managed/
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project/boot/
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project/plugins/project/
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# Scala-IDE specific
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.scala_dependencies
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.worksheet
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*.dat
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.idea/*
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.idea_modules/*
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*.iml
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### Python
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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# C extensions
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*.so
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#core/metastore_db/*
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inst/java/
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*~
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*metastore_db/
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nohup.out
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#spark/conf/local
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core/target
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spark/target
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example/target
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project/target
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core/ddf-runtime
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examples/target/streams
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core/target/streams
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project/target/streams
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spark/target/streams
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R/package/inst/java
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# R stuffs
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.Rproj.user
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#Rserve files
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pa/rlibs/Rserve/*
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pa/conf/local/hive-site.xml
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spark/conf/local/hive-site.xml
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.Rhistory
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.RData

LICENSE

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same "printed page" as the copyright notice for easier
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identification within third-party archives.
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Copyright 2014, Adatao, Inc.
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Copyright {yyyy} {name of copyright owner}
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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README.md

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DDF
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===
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Distributed DataFrame: Productivity = Power x Simplicity
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For Big Data Scientists & Engineers
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# DDF - Distributed DataFrame
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DDF aims to make Big Data easy yet powerful, by bringing together

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