For web apps that receive JSON and simply write it to a queue, database, or other storage, try not to ever parse the JSON if you can. This may seem obvious, but it necessarily isn’t. So use gzip wherever possible when communicating with your web services. Since JSON is just simple text, you can expect to get up to 90% compression. Improved Performance using JSON Streaming This is a little more efficient and preferred where possible. Most JSON parsing libraries can read straight from a stream instead of a string. I haven’t tested it myself but I have also heard good things about Jil which is designed entirely for speed by StackExchange’s team. Overall most features and flexibility: Json.NET Here are my results from doing some simple benchmarks from a test app ( View on GitHub). If you do a lot of parsing and really care about performance, FastJsonParser is a lot faster than anything else I have tried. This is based on my own testing and I encourage you to do the same. But ServiceStack, FastJsonParser () and even the built in DataContractJavascriptSerializer may be faster or provide specific features you may need depending on the scenario. In ASP.NET the most popular JSON library is Json.NET (Newtonsoft). You may need multiple JSON libraries for optimal performance and features NET for most of our services, most of these tips apply to other programming languages as well. We have compiled a list of some common JSON performance tips. Although originally derived from the JavaScript scripting language, JSON is now a language-independent data format and code for parsing and generating JSON data is readily available in many programming languages.Īt Stackify, we use JSON extensively for REST APIs, serializing messages to queues, and much more. JSON is easy to work with and has become the standard data format for virtually everything. Equivalent to FETCH NEXT FROM M圜ursor INTO. (VistaMember),(ResponseHTTPStatusCode),(ResponseHeaders),(ResponseBody),(LogCreated) IntoĪLTER TABLE #MyTempTable ADD OriginalID INT Select IDENTITY(int, 1, 1) AS ,(sessionid),(AbsolutePath),(query),(RequestHeaders),(RequestBody),(PartnerId), Thanks for the help so farĬan't get it to work tho as doing something lie this will complain about cannot insert identity Insert into an unknown table using select Try commenting out the LIKE as well, and seeing how much that improves things - although that's only good just-for-comparison of the baseline, of course. There is more to the tuning process than this, but they are my first "basic" steps to getting a handle on how things might be improved. a column which is NOT in the Clustered Index) I would investigate why that is.Īlso look at which tables/indexes use a SCAN rather than a SEEK For example, if the Clustered Index is used when there is a dedicated index on the main column in your query (i.e. In the SHOWPLAN I would look for which index is used for each table(s) in the query, and if that seems like the best choice. I would do the statistics first, to get the base line. Run from the SHOWPLAN comment for the Query Plan (the query is NOT run), and from the STATISTICS comment for the number of scans and the amount of I/O (the query IS run, so this will be the actual run-time for the query). SET STATISTICS IO OFF SET STATISTICS TIME OFF SET STATISTICS PROFILE OFF SET STATISTICS IO ON SET STATISTICS TIME ON The wildcard on will be slow, it would be helped if there was an index on AND the selectivity of is reasonably good (it you have thousands of rows for each value, for THAT table, then SQL may choose not to use the index and table-scan every row instead - SET SHOWPLAN_TEXT ON Select something from Requestbody where where id = xxx and Requestbody like '%somesearch%'
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