digitalmars.D.learn - how to harvest the results of tasks from a taskpool?
- Martin (25/25) Jul 05 2017 Hi,
- Martin Tschierschke (42/67) Jul 05 2017 I tested a much simpler approach with the following
Hi, i have a coulpe of different machines with MySQL Servers running on it. Now, i want to execute queries for all Databases at the same time and collect the Result to process it. I am new to the parallelism - so maybe i understand something totaly wrong. What i tring is something like this: <code> { auto tPool = new TaskPool(); forach(server ; servers) { auto task = task!queryWorker(query); tPool.put(task); } tPool.finish(true); //--------> how to collect the results now? <------- } row[] queryWorker(string query) { //rows = result of the query return rows; } </code> btw.. how to markup code in this forum?
Jul 05 2017
On Wednesday, 5 July 2017 at 13:55:22 UTC, Martin wrote:Hi, i have a coulpe of different machines with MySQL Servers running on it. Now, i want to execute queries for all Databases at the same time and collect the Result to process it. I am new to the parallelism - so maybe i understand something totaly wrong. What i tring is something like this: <code> { auto tPool = new TaskPool(); forach(server ; servers) { auto task = task!queryWorker(query); tPool.put(task); } tPool.finish(true); //--------> how to collect the results now? <------- } row[] queryWorker(string query) { //rows = result of the query return rows; } </code> btw.. how to markup code in this forum?I tested a much simpler approach with the following setup/structure?: // a shared array of results where each result is again an array; Rows results[]; // using parallel foreach foreach(i,server;servers.parallel){ result[i] = request(server).array;; } Now every array of rows is accessible in result[]? Tested this construct with parallel curl requests: time ./parallel_curl Site www.dlang.org. Page has length:31607 Site forum.dlang.org. Page has length:24358 Site code.dlang.org. Page has length:36477 Site www.google.com. Page has length:10628 real 0m0.836s user 0m0.137s sys 0m0.034s Without parallel: real 0m2.424s user 0m0.722s sys 0m0.209s This is the code: import std.stdio; import std.net.curl; import std.parallelism; void main() { enum string[] tospider = ["www.dlang.org","forum.dlang.org","code.dlang.org","www.google.com"]; char[][tospider.length] results; foreach(i,site;tospider.parallel){ results[i] = get(site); } foreach(i,e;results){ writeln("Site ", tospider[i],". Page has length:",e.length); } } Will try to use this approach to collect some elastic seach results and look if it speeds up on an 8 core machine.
Jul 05 2017