hkpeaks commented on issue #35688:
URL: https://github.com/apache/arrow/issues/35688#issuecomment-1661330659

   I plan use Apache Arrow compatible python libraries to support building a 
new ETL Framework (it look like an alternative version of SQL statement which 
specialized in dealing with file, tcp stream, in-memory table and bigdata).
   
   Example: 
   
   UserDefineFunctionName: SourceFile.ext/ Table / SQL.Table ~ ResultFile.ext 
/Table / SQL.Table
   | Command: Setting
   
   ExpandFile: Fact.csv ~ 1BillionRows.csv
   | ExpandFactor: 123
   
   JoinScenario1: 1BillionRows.csv ~ Test1Results.csv
   | JoinTable: Quantity, Unit_Price => InnerJoin(Master)Multiply(Amount)
   | OrderBy: Date(D) => CreateFolderLake(Shop)
   | Select: Date,Shop,Style,Product,Quantity,Amount
   
   BuildKeyValueTable: Master.csv ~ KeyValueTable
   | BuildKeyValue: Product, Style
   
   JoinScenario2: 1BillionRows.csv ~ Test2AResults.csv
   | JoinKeyValue: Product, Style => AllMatch(KeyValueTable)
   | AddColumn: Quantity, Unit_Price => Multiply(Amount)
   | Filter: Amount(Float > 50000)
   | GroupBy: Product, Style => Count() Sum(Quantity) Sum(Amount)
   | OrderBy: Shop(A)Product(A)Date(D)
   
   SplitFile: Test1Results.csv ~ FolderLake
   | CreateFolderLake: Shop
   
   FilterFolder: Outbox/FolderLake/S15/*.csv ~ Result-FilterFolderLake.csv
   | Filter: Product(222..888) Style(=F)
   
   ReadSample2View: Outbox/Result-FilterFolderLake.csv ~ SampleTable
   | ReadSample: StartPosition%(0) ByteLength(100000)
   | View
   


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