This sample assumes the folder is named "output".Īdd the following script and build a flow using the steps given to try the sample yourself! Sample code: Insert comma-separated values into a workbook /** Prices analysis from many providers (MTGStock, MTGOldfish. Extract the files into a folder in your OneDrive. Deck Editor (construct, sealed) and import tool from many websites (tappedout, deckstat,mtggoldfish,mtgTop8.) Collection manager (stock, foil, etched, condition.) Thematic Dashboards : personnalize your interested PKI in multiple dashboard. csv files and pass their contents to the script.ĭownload convert-csv-example.zip to get the Template.xlsx file and two sample.
Create a Power Automate flow to read the. Create an Office Script to parse the CSV data into a range. csv extension in a OneDrive folder and an Office Script to copy the data from the. It uses a Power Automate flow to find files with the. This solution automates the process of converting those CSV files to Excel workbooks in the. Assuming you are using Java 8 or later, the Stream API can be very helpful.Many services export data as comma-separated value (CSV) files. This will require changing the method signature to use a return type other than List. This means that each line of the file is processed and then passed directly to the output, without collecting all of the lines in memory in between. Otherwise, the best way to deal with large amounts of data in a bounded amount of memory is to use a streaming approach. If you have enough memory available on the machine to assign a heap size large enough to hold the entire contents, that will be the simplest solution, as it won't require changing the code. Each line may not consume much memory, but multiplied by millions of lines, it all adds up. The memory consumption would be less from the replace and split operations, and more from the fact that the entire contents of the file need to be read into memory in this approach. The main problem is using too much heap memory, and the performance problem is likely to be due to excessive garbage collection when the remaining available heap is very small (but it's best to measure and profile to determine the exact cause of performance problems). I don't think that splitting this work onto multiple threads is going to provide much improvement, and may in fact make the problem worse by consuming even more memory. Do you know of a different approach to split at comas and replace the double quotes in each CSV line ? Would StringBuilder be of any healp here ? What about StringTokenizer ? How could I reduce the amount of heap memory used in the process ? Is the multithread implementation with Callable correct ? How could I improve the speed of the CSV reading ? Other than that the api is running out of heap memory when running on the server, I know that a solution would be to enhance the amount of available memory but I suspect that the replace() and split() operations on strings made in the Callable(s) are responsible for consuming a large amout of heap memory. Take a look at what needs to be changed (changing the name of the columns, deleting unnecessary columns, etc) and do that to what you got from decked builder. Five or six from different sets worked for me Then export it in csv. To improve speed processing, I tried to implement multithreading with Callable(s) but I am not familiar with that kind of concept, so the implementation might be wrong. Go to deckbox and add some cards to your inventory. 
#DECKED BUILDER CONVERT CSV TO COLL CODE#
The code works fine on my local machine but it is very slow : it takes about 20 seconds to process 450 columns and 40 000 lines. I am not guaranteed to have the same header between files (each file can have a completly different header than another), so I have no way to create a dedicated class which would provide mapping with the CSV headers.Ĭurrently the api controller is calling a csv service which reads the CSV data using a BufferReader. It has to read big CSV files which will contain more than 500 columns and 2.5 millions lines each. I am currently working on a spring based API which has to transform csv data and to expose them as json.
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