Spring Data Reactive MongoDb :: Date Aggeration with Timezone Get link Facebook Twitter Pinterest Email Other Apps By Karma May 09, 2020 A short example on how to aggravate by date with a different timezone using Spring Data Reactive Mongodb. Code Snippet on github public Flux getHourlyReport() { DateOperators.Timezone timezone = DateOperators.Timezone.valueOf("America/New_York"); Aggregation aggregation = Aggregation.newAggregation(Aggregation.project() .and(DateOperators.Hour.hour("$tweet.createdAt") .withTimezone(timezone)) .as("hour") , Aggregation.group("hour").count().as("sum")); Flux data = this.mongoTemplate.aggregate(aggregation, "realTweets", Map.class); return data; } Get link Facebook Twitter Pinterest Email Other Apps Comments
SSIS Package : Export Data from Database, Daily to New Excel Without Using Script Task By AB June 06, 2012 Export data from database to excel sheet with new excel per day SSIS => SQL Server Integration Services, is used for ETL (Extract, Transform and Load) type of work. It is advanced version of DTS we can say. Here we can schedule packages as jobs and it will execute without human intervention. In this article we will export the data from SQL database table to excel sheet day wise. To start with this you will need to install SQL Server 2008 with BIDS (Business Intelligence Development Studio) Now moving forward the first step would be go to File => New Project => Select “Business Intelligence Projects” from left panel and “Integration Service Project” from right panel. Give proper name and save at desired location. On OK click, it will open Package.dtsx. Create a Template folder somewhere on your hard drive. In that folder create a sample excel with just the headers that you want in the final excel. We will use this template to create new excel every day Read more
Getting Started With ForkJoinPool - Map & Reduce of Java By GD May 25, 2012 CodeProject ForkJoinPool - Java's Map & Reduce ForkJoinPool ::FJP is a executor service for Fork-Join Taks or tasks which can computed using divide and conqor or we can say FJP is inbuild Map & Reduce framework in Java. FJP implements work-steal so all threads try to find and execute task submitted by other tasks in FJP or external program. FJP try to maintain active threads as per number of processor available. FJP provides below methods to submit task ::==> Call Type External Task Clients i.e. main method Inner Task Divide and Conquer Calls Call from non-fork/join clients Call from within fork/join computations Arrange async execution execute(ForkJoinTask) ForkJoinTask.fork() Await and obtain result invoke(ForkJoinTask) ForkJoinTask.invoke() Arrange exec and obtain Future submit(ForkJoinTask) ForkJoinTask.fork() (ForkJoinTasks are Futures) Read more
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