sql-execution-plan

问题 As I know, heap tables are tables without clustered index and has no physical order. I have a heap table "scan" with 120k rows and I am using this select: SELECT id FROM scan If I create a non-clustered index for the column "id", I get 223 physical reads . If I remove the non-clustered index and alter the table to make "id" my primary key (and so my clustered index), I get 515 physical reads . If the clustered index table is something like this picture: Why Clustered Index Scans workw like

问题 We have a query that is taking around 5 sec on our production system, but on our mirror system (as identical as possible to production) and dev systems it takes under 1 second. We have checked out the query plans and we can see that they differ. Also from these plans we can see why one is taking longer than the other. The data, schame and servers are similar and the stored procedures identical. We know how to fix it by re-arranging the joins and adding hints, However at the moment it would be

问题 I am calling SQL Server 10 from Entity Framework in C# and want to get a query hint into the request. The database has indexes which operated normally from SQL run in Management Studio, but when calling the command from C# using Entity Framework in Visual Studio, the query planner chooses a full scan when there is already an index. I am creating dynamic predicates to request data in the following form: data.attributeText = data.vegaDB.attributeText.AsExpandable().Where(parentPredicate.Compile

问题 I have the following query.explain(1)-Output. It is a verbose output and my question is how to read that. How is the order of the operations? Does it starts with GEO_NEAR_2DSPHERE or with LIMIT? What does the field advanced express? And most important, where is this documented? Could not find this in the mongoDB-manual :( Query: db.nodesWays.find( { geo:{ $nearSphere:{ $geometry:{ type: "Point", coordinates: [lon, lat] } } }, "amenity":"restaurant" }, {name:1} ).limit(10).explain(1) The

问题 The actual execution plan for my Azure SQL Database stored procedure indicated the following warning: So I went and added a persisted calculated column in dbo.Interest_rate_changes like this: [Effective_date] AS (CONVERT([date],CONVERT([nchar](8),[Effective_date_int]),(112))) PERSISTED NOT NULL I then replaced all references to Interest_date_int in the stored procedure with references to Interest_date. I ran the query again but the same warning appeared in the actual execution plan, even

问题 We see an issue occasionally. Stored procedure running a SQL runs very slow. Same SQL when run from command line runs very fast. It seems stored procedure uses a different path. The workaround for us is to drop and recreate the procedure, after which it picks up the right plan. Is there a way to execute a stored procedure with an instruction to regenerate execution plan at run time, so as to get the best plan every time. 回答1: You probably don't want to recompile plans every time you call your

问题 On a powerful machine the SQL Server query is running too slowly. In the execution plan I can see that most of the time spent goes to a "Lazy Index Spooling" process. In the query some aggregate functions are being used for calculation of values. How can I speed-up the query (machine resources are enough)? Thanks in advance. 来源： https://stackoverflow.com/questions/26314632/query-is-extremely-slow-due-to-lazy-index-spool

问题 Say I have 2 functions using third one. Say function check_permission(user_id) is used by get_company(user_id) and get_location(user_id). How would execution plan cache work? I mean would it be making separate execution plans for check_permission and get_company functions or would it be one plan for get_company? There is a chance that execution plan will be more efficient if it is built for get_company and get_location individually even if they are both using check_permission function. 回答1:

问题 I may have a slight feeling as to what is going on, but I thought I'd ask to get confirmation, and potentially look at an alternative. As a slight background, I've written a C# application that is providing a small front end to a stored procedure. The procedure contains a number of temporary table inserts from other stored procedures (and one table valued udf), and some xml processing. In order to get a sense of how far along I am in the stored procedure, I'm subscribing to the InfoMessage

问题 I have noticed that Apache Flink does not optimise the order in which the tables are joined. At the moment, it keeps the user-specified join order (basically, it takes the the query literally). I suppose that Apache Calcite can optimise the order of joins but for some reason these rules are not in use in Apache Flink. If, for example, we have two tables ' R ' and ' S ' private val tableEnv: BatchTableEnvironment = TableEnvironment.getTableEnvironment(env) private val fileNumber = 1 tableEnv