There are about as many opinions and resources on SQL Spatial Index Tuning as there are on why the use of a Sequential GUID is good or bad. There's The Black Art Of Spatial Index Tuning In SQL Server | boomphisto , ArcGIS Help 10.1, Spatial Indexing Overview , Spatial Indexing: From 4 Days to 4 Hours - CSS SQL Server Engineers - Site Home - MSDN Blogs, sp_help_spatial_geography_histogram and Indexing geography data in SQL Server Denali | Alastair Aitc... , Basic Multi-Level Grids - Isaac @ MSDN - Site Home - MSDN Blogs , http://social.technet.microsoft.com/wiki/contents/articles/9694.tuning-spatial-point-data-queries-in... , and of course, if you've ever struggled with a poorly-performing spatial index and posted about it on the internet, chances are you got a reply from this guy.
Unfortunately, most of us are not database programmers, nor do we dream in SQL syntax. SQL is like learning French by reading a Chinese dictionary. I don't know about you, but I can't make heads or tails of one single line of SQL code. I'm happy to copy other peoples SQL snippets and hack them up 'till I get them to work. I particularly love this statement from ArcGIS Help: "If you create your data through ArcGIS for Desktop, the spatial grid index is calculated for you." That's like saying "If you put your key in the ignition, your car will drive to the store, get milk, and NOT kill a raccoon on the way". Unless your a Massachusetts driver, there are obviously a few things you have to tweak, such as turn the steering wheel and press the gas paddle in endlessly unique combinations in order to get to the milk store and swerve to avoid the raccoon. The same goes for SQL Spatial Indexes in a SDE Database. Just because the software enables them out of the box by no means implies that the index is optimized for your particular data environment.
Out of the box, ArcGIS creates a spatial index with 16 Cells Per Object with all four levels set to Medium Grid Levels.
Notice how the storage type is Goemetry, which some of you are discovering is the "New" ESRI default storage format.
Let's see how the "Out of the Box" spatial index performs. One way to test a spatial index "Quick and Easy" is with the Spatial Index Stored Procedures.
CREATE SPATIAL INDEX --THIS IS THE DEFAULT NAME OF THE INDEX --CREATED BY ARCGIS [S1169_idx] ON --AND THIS IS THE NAME OF TABLE --SUPPLIED BY THE USER IN ARCGIS --AT CREATION TIME [dbo].[TEST_GEOM] ( [SHAPE] )USING GEOMETRY_GRID WITH (BOUNDING_BOX =(227166.13, 3925740.74, 314851.6915, 3968047.64), GRIDS =( LEVEL_1 = MEDIUM, LEVEL_2 = MEDIUM, LEVEL_3 = MEDIUM, LEVEL_4 = MEDIUM), CELLS_PER_OBJECT = 16, PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, SORT_IN_TEMPDB = OFF, --DROP_EXISTING = ON ALLOWS US TO DO THIS ALL --DAY WITHOUT MESSING WITH DROPPING THE IDX DROP_EXISTING = ON, ONLINE = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON, FILLFACTOR = 100) ON [PRIMARY] GO DECLARE @geom geometry --THE POLYGON IS AN AREA SMALLER THAN THE BOUNDING BOX SET @geom = GEOMETRY::STGeomFromText('POLYGON ((247804.201 3943957.896, 29932.568 3943963.210, 247671.344 3942876.441, 247684.630 3943652.325,247804.201 3943957.896))', 26917)jjj exec sp_help_spatial_geometry_index 'TEST_GEOM', 'S1169_idx', 1, @geom
There's a WHOLE lot of output. The first thing my eye spies is
Primary_Filter_Efficiency | 19.634703196347 |
and
Internal_Filter_Efficiency | 0 |
I'm no expert on SQL or spatial indexes, but I don't think those numbers look good. No wonder my draw times are slow, spatial queries are sluggish, and in general, the database is performing horribly. Every single ArcGIS-created table has the same index parameters!
Just for giggle, lets change the cells per object by altering just this in the above code snippet:
CELLS_PER_OBJECT = 4096
And look at the increase in efficiencies!
Internal_Filter_Efficiency | 76.7441860465116 |
Primary_Filter_Efficiency | 91.4893617021277 |
Again, I'm claiming to be no expert at SQL Spatial Index Tuning, but I think I'm on to something here. As it turns out, my test data consists of "Very Complex Line Strings", which, if you're not living under the GIS rock, that's what all of your data is. Coincidentally, using value of 8192 for Cells Per Object in this scenario is a good starting point.
But there's a lot (lots and lots) of values between 16 and 8092, and then there's all the permutations of Low, Medium, and High that could be tested to determine the spatial index that is likely to give you the best performance most of the time. What if there was a way to automatically test spatial index settings and magically determine which parameters best fit your data scenario?
Enter the SDE Hacker....
I stumbled across this geospatial - Selecting a good SQL Server 2008 spatial index with large polygons - Stack Overflow post where someone had posted a SQL stored procedure that will loop through Cell Sizes and Grid Levels to report Spatial Query results for every permutation (user supplied). Being the tinker that I am, I of course broke the code trying to add a bunch of output. Finally got it working. Here it is:
--ORIGINAL SQL CODE FROM --http://stackoverflow.com/users/2250424/greengeo --MODIFIFIED TO INCLUDE SPATIAL INDEX HELP OUTPUT --IN TABLE --!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! --LOOK FOR THE EXCLAMATION POINTS IN THIS CODE --THERE ARE SEVERAL USER-SUPPLIED VARIABLES THAT MUST --BE INPUT FOR THIS SP TO WORK --!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! USE DATBASE GO CREATE PROCEDURE dbo.sp_tune_spatial_index ( @tabnm VARCHAR(MAX), -- This parameter stores the name of the spatial table for which you are tuning the index @idxnm VARCHAR(MAX), -- This parameter stores the name of the spatial index of the named table @min_cells_per_obj INT, -- Minimum Cells Per Object to test on. Suggested to start at 2. @max_cells_per_obj INT, -- Maximum Cells Per Object to test on. /* The test requires two geometry instances to use in test query 1 and 2. The first one should cover the area of default extent. The second should cover an area roughly the size of the area shown when zoomed in, panning around. It is required that the variable store a string that will create the geometry instance since this will be done within the procedure and cannot be a variable of type: GEOMETRY. The SRID of these instances must match that of the table you are testing. */ @testgeom1 VARCHAR(MAX), -- This parameter stores the first geometry instance creation string that will be used in the test @testgeom2 VARCHAR(MAX) -- This parameter stores the second geometry instance creation string that will be used in the test ) AS SET NOCOUNT ON; /* Prior to running this procedure, two tables are required. These tables are created here to prepare for running the procedure. */ PRINT 'Checking for required tables...' IF EXISTS(SELECT 1 FROM sysobjects WHERE name IN ('cell_opt_perm', 'spat_idx_test_result')) BEGIN PRINT '... The "cell_opt_perm" and "spat_idx_test_result" tables exist.' END ELSE BEGIN PRINT '... Creating "cell_opt_perm" and "spat_idx_test_result" tables.' CREATE TABLE cell_opt_perm( [perm_id] [smallint] NOT NULL, [permutation] [nvarchar](4) NOT NULL, [level1] [nvarchar](6) NOT NULL, [level2] [nvarchar](6) NOT NULL, [level3] [nvarchar](6) NOT NULL, [level4] [nvarchar](6) NOT NULL ) INSERT INTO cell_opt_perm ([perm_id], [permutation], [level1], [level2], [level3], [level4]) VALUES (1,'LLLL','LOW','LOW','LOW','LOW'), (2,'LLLM','LOW','LOW','LOW','MEDIUM'), (3,'LLLH','LOW','LOW','LOW','HIGH'), (4,'LLML','LOW','LOW','MEDIUM','LOW'), (5,'LLMM','LOW','LOW','MEDIUM','MEDIUM'), (6,'LLMH','LOW','LOW','MEDIUM','HIGH'), (7,'LLHL','LOW','LOW','HIGH','LOW'), (8,'LLHM','LOW','LOW','HIGH','MEDIUM'), (9,'LLHH','LOW','LOW','HIGH','HIGH'), (10,'LMLL','LOW','MEDIUM','LOW','LOW'), (11,'LMLM','LOW','MEDIUM','LOW','MEDIUM'), (12,'LMLH','LOW','MEDIUM','LOW','HIGH'), (13,'LMML','LOW','MEDIUM','MEDIUM','LOW'), (14,'LMMM','LOW','MEDIUM','MEDIUM','MEDIUM'), (15,'LMMH','LOW','MEDIUM','MEDIUM','HIGH'), (16,'LMHL','LOW','MEDIUM','HIGH','LOW'), (17,'LMHM','LOW','MEDIUM','HIGH','MEDIUM'), (18,'LMHH','LOW','MEDIUM','HIGH','HIGH'), (19,'LHLL','LOW','HIGH','LOW','LOW'), (20,'LHLM','LOW','HIGH','LOW','MEDIUM'), (21,'LHLH','LOW','HIGH','LOW','HIGH'), (22,'LHML','LOW','HIGH','MEDIUM','LOW'), (23,'LHMM','LOW','HIGH','MEDIUM','MEDIUM'), (24,'LHMH','LOW','HIGH','MEDIUM','HIGH'), (25,'LHHL','LOW','HIGH','HIGH','LOW'), (26,'LHHM','LOW','HIGH','HIGH','MEDIUM'), (27,'LHHH','LOW','HIGH','HIGH','HIGH'), (28,'MLLL','MEDIUM','LOW','LOW','LOW'), (29,'MLLM','MEDIUM','LOW','LOW','MEDIUM'), (30,'MLLH','MEDIUM','LOW','LOW','HIGH'), (31,'MLML','MEDIUM','LOW','MEDIUM','LOW'), (32,'MLMM','MEDIUM','LOW','MEDIUM','MEDIUM'), (33,'MLMH','MEDIUM','LOW','MEDIUM','HIGH'), (34,'MLHL','MEDIUM','LOW','HIGH','LOW'), (35,'MLHM','MEDIUM','LOW','HIGH','MEDIUM'), (36,'MLHH','MEDIUM','LOW','HIGH','HIGH'), (37,'MMLL','MEDIUM','MEDIUM','LOW','LOW'), (38,'MMLM','MEDIUM','MEDIUM','LOW','MEDIUM'), (39,'MMLH','MEDIUM','MEDIUM','LOW','HIGH'), (40,'MMML','MEDIUM','MEDIUM','MEDIUM','LOW'), (41,'MMMM','MEDIUM','MEDIUM','MEDIUM','MEDIUM'), (42,'MMMH','MEDIUM','MEDIUM','MEDIUM','HIGH'), (43,'MMHL','MEDIUM','MEDIUM','HIGH','LOW'), (44,'MMHM','MEDIUM','MEDIUM','HIGH','MEDIUM'), (45,'MMHH','MEDIUM','MEDIUM','HIGH','HIGH'), (46,'MHLL','MEDIUM','HIGH','LOW','LOW'), (47,'MHLM','MEDIUM','HIGH','LOW','MEDIUM'), (48,'MHLH','MEDIUM','HIGH','LOW','HIGH'), (49,'MHML','MEDIUM','HIGH','MEDIUM','LOW'), (50,'MHMM','MEDIUM','HIGH','MEDIUM','MEDIUM'), (51,'MHMH','MEDIUM','HIGH','MEDIUM','HIGH'), (52,'MHHL','MEDIUM','HIGH','HIGH','LOW'), (53,'MHHM','MEDIUM','HIGH','HIGH','MEDIUM'), (54,'MHHH','MEDIUM','HIGH','HIGH','HIGH'), (55,'HLLL','HIGH','LOW','LOW','LOW'), (56,'HLLM','HIGH','LOW','LOW','MEDIUM'), (57,'HLLH','HIGH','LOW','LOW','HIGH'), (58,'HLML','HIGH','LOW','MEDIUM','LOW'), (59,'HLMM','HIGH','LOW','MEDIUM','MEDIUM'), (60,'HLMH','HIGH','LOW','MEDIUM','HIGH'), (61,'HLHL','HIGH','LOW','HIGH','LOW'), (62,'HLHM','HIGH','LOW','HIGH','MEDIUM'), (63,'HLHH','HIGH','LOW','HIGH','HIGH'), (64,'HMLL','HIGH','MEDIUM','LOW','LOW'), (65,'HMLM','HIGH','MEDIUM','LOW','MEDIUM'), (66,'HMLH','HIGH','MEDIUM','LOW','HIGH'), (67,'HMML','HIGH','MEDIUM','MEDIUM','LOW'), (68,'HMMM','HIGH','MEDIUM','MEDIUM','MEDIUM'), (69,'HMMH','HIGH','MEDIUM','MEDIUM','HIGH'), (70,'HMHL','HIGH','MEDIUM','HIGH','LOW'), (71,'HMHM','HIGH','MEDIUM','HIGH','MEDIUM'), (72,'HMHH','HIGH','MEDIUM','HIGH','HIGH'), (73,'HHLL','HIGH','HIGH','LOW','LOW'), (74,'HHLM','HIGH','HIGH','LOW','MEDIUM'), (75,'HHLH','HIGH','HIGH','LOW','HIGH'), (76,'HHML','HIGH','HIGH','MEDIUM','LOW'), (77,'HHMM','HIGH','HIGH','MEDIUM','MEDIUM'), (78,'HHMH','HIGH','HIGH','MEDIUM','HIGH'), (79,'HHHL','HIGH','HIGH','HIGH','LOW'), (80,'HHHM','HIGH','HIGH','HIGH','MEDIUM'), (81,'HHHH','HIGH','HIGH','HIGH','HIGH') CREATE TABLE spat_idx_test_result( [perm_id] [int] NOT NULL, [num_cells] [int] NOT NULL, [permut] [nvarchar](4) NOT NULL, [g1t1] [bigint] NULL, [g1t2] [bigint] NULL, [g1t3] [bigint] NULL, [g1t4] [bigint] NULL, [g2t1] [bigint] NULL, [g2t2] [bigint] NULL, [g2t3] [bigint] NULL, [g2t4] [bigint] NULL, [PF_EFF][float] NULL, [IF_EFF][float] NULL, [GRIDL1] [int] NULL, [GRIDL2] [int] NULL, [GRIDL3] [int] NULL, [GRIDL4] [int] NULL, [TPIR] [bigint] NULL, [TPIP] [bigint] NULL, [ANOIRPBR] [bigint] NULL, [TNOOCILFQ] [bigint] NULL, [TNOOCIL3FQ] [bigint] NULL, [TNOOCIL4FQ] [bigint] NULL, [TNOOCIL0II] [bigint] NULL, [TNOOCIL4II] [bigint] NULL, [TNOIOIL3FQ] [bigint] NULL, [TNOIOIL4FQ] [bigint] NULL, [ITTCNTLGP] [float] NULL, [INTTTCNTLGP] [float] NULL, [BTTCNTLGP] [float] NULL, [ACPONTLGP] [float] NULL, [AOPG] [float] NULL, [NORSBPF] [bigint] NULL, [NORSBIF] [bigint] NULL, [NOTSFIC] [bigint] NULL, [NORO] [bigint] NULL, [PORNBPF] [float] NULL, [POPFRSBIF] [float] NULL ) INSERT INTO dbo.spat_idx_test_result VALUES (0,16,0,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL,NULL) END /* delete all rows from "spat_idx_test_result" table. This makes it ready to stuff in new results. !!!WARNING!!! if your test was interupted, the table will be cleared out and the test will begin from the beginning. You could try to modify this to start where you left off but I didn't have time and this worked well enough for me. */ DELETE FROM spat_idx_test_result WHERE perm_id != 0 /* set up counters */ DECLARE @a1 INT DECLARE @a2 INT DECLARE @a3 INT DECLARE @a4 INT /* set up variables to hold high/medium/low values and permutation to use in rebuilding the spatial index and recording stats */ DECLARE @lev1 VARCHAR(6) DECLARE @lev2 VARCHAR(6) DECLARE @lev3 VARCHAR(6) DECLARE @lev4 VARCHAR(6) DECLARE @permut VARCHAR(6) DECLARE @num_cell VARCHAR(4) DECLARE @time_str VARCHAR(20) DECLARE @perm_id VARCHAR(20) DECLARE @x xml DECLARE @pf_eff FLOAT /* create variables to hold timestamps for beginning and ending of test queries */ DECLARE @start_t DATETIME DECLARE @end_t DATETIME DECLARE @elapse_t INT /* begin looping through cell option permutations */ SET @a1 = @min_cells_per_obj WHILE @a1 <= @max_cells_per_obj BEGIN SET @a2 = 1 PRINT 'Started Testing for ' +CAST(@a1 AS VARCHAR(10)) +' cells per object' WHILE @a2 < 82 BEGIN SELECT @lev1 = level1, @lev2 = level2, @lev3 = level3, @lev4 = level4 FROM cell_opt_perm WHERE perm_id = @a2 SET @permut = '''' +(SELECT permutation FROM cell_opt_perm WHERE perm_id = @a2) +'''' EXEC (' CREATE SPATIAL INDEX ' +@idxnm +' ON ' +@tabnm +' ( [SHAPE] ) USING GEOMETRY_GRID WITH ( --!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! --MAKE SURE YOU EDIT THE BOUNDING BOX TO BE EXACTLY EQUAL TO THE BOUNDING --BOX OF YOUR SPATIAL TABLE --!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! BOUNDING_BOX =(227166.13, 3925740.74, 314851.6915, 3968047.64), GRIDS =(LEVEL_1 = ' +@lev1 +' ,LEVEL_2 = ' +@lev2 +' ,LEVEL_3 = ' +@lev3 +' ,LEVEL_4 = ' +@lev4 +' ), CELLS_PER_OBJECT = ' +@a1 +' , PAD_INDEX = OFF, SORT_IN_TEMPDB = OFF, DROP_EXISTING = ON, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON, FILLFACTOR = 100 ) ON [PRIMARY] ' ) PRINT 'Re-built index to ' +@permut SET @a3 = 1 SET @a4 = 1 WHILE @a3 < 5 BEGIN SET @start_t = GETDATE() EXEC ( 'CREATE TABLE #tmp_tab (shp GEOMETRY) DECLARE @g1 GEOMETRY SET @g1 = ' +@testgeom1 +' INSERT #tmp_tab (shp) SELECT r.Shape AS shp FROM ' +@tabnm +' r WHERE r.SHAPE.STIntersects(@g1) = 1 DROP TABLE #tmp_tab' ) SET @end_t = GETDATE() SET @elapse_t = (SELECT DATEDIFF(MS, @start_t, @end_t)) SET @num_cell = CAST(@a1 AS VARCHAR(6)) SET @time_str = CAST(@elapse_t AS VARCHAR(20)) IF @a3 = 1 BEGIN IF (SELECT TOP 1 perm_id FROM spat_idx_test_result) IS NULL BEGIN SET @perm_id = 1 END ELSE BEGIN SET @perm_id = CAST((SELECT MAX(perm_id+1) FROM spat_idx_test_result) AS VARCHAR(20)) END EXEC ( ' INSERT INTO spat_idx_test_result (perm_id, num_cells, permut, g1t' +@a3 +') VALUES (' +@perm_id +', ' +@num_cell +', ' +@permut +', ' +@time_str +')' ) END ELSE EXEC ( ' UPDATE spat_idx_test_result SET num_cells = ' +@num_cell +', permut = ' +@permut +', g1t' +@a3 +' = ' +@time_str +' WHERE perm_id = ' +@perm_id ) SET @a3 = @a3 + 1 END WHILE @a4 < 5 BEGIN SET @start_t = GETDATE() EXEC ( 'CREATE TABLE #tmp_tab (shp GEOMETRY) DECLARE @g2 GEOMETRY SET @g2 = ' +@testgeom2 +' INSERT #tmp_tab (shp) SELECT r.Shape AS shp FROM ' +@tabnm +' r WHERE r.SHAPE.STIntersects(@g2) = 1 DROP TABLE #tmp_tab' ) SET @end_t = GETDATE() SET @elapse_t = (SELECT DATEDIFF(MS, @start_t, @end_t)) SET @num_cell = CAST(@a1 AS VARCHAR(6)) SET @time_str = CAST(@elapse_t AS VARCHAR(20)) EXEC ( ' DECLARE @geom geometry DECLARE @x xml DECLARE @PFVALUE float DECLARE @IFVALUE float DECLARE @GRIDL1VALUE int DECLARE @GRIDL2VALUE int DECLARE @GRIDL3VALUE int DECLARE @GRIDL4VALUE int DECLARE @TPIRVALUE bigint DECLARE @TPIPVALUE bigint DECLARE @ANOIRPBRVALUE bigint DECLARE @TNOOCILFQVALUE bigint DECLARE @TNOOCIL0IIVALUE bigint DECLARE @TNOOCIL4IIVALUE bigint DECLARE @TNOOCIL3FQVALUE bigint DECLARE @TNOOCIL4FQVALUE bigint DECLARE @TNOIOIL3FQVALUE bigint DECLARE @TNOIOIL4FQVALUE bigint DECLARE @ITTCNTLGPVALUE float DECLARE @INTTTCNTLGPVALUE float DECLARE @BTTCNTLGPVALUE float DECLARE @ACPONTLGPVALUE float DECLARE @AOPGVALUE float DECLARE @NORSBPFVALUE bigint DECLARE @NORSBIFVALUE bigint DECLARE @NOTSFICVALUE bigint DECLARE @NOROVALUE bigint DECLARE @PORNBPFVALUE float DECLARE @POPFRSBIFVALUE float --!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! --MAKE SURE YOU EDIT GEOMETRY VARIABLE BELOW TO REPRESENT A POLYGON --THAT IS WITHIN YOUR BOUNDING BOX --!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! SET @geom = GEOMETRY::STGeomFromText(''POLYGON ((247804.201 3943957.896, 29932.568 3943963.210, 247671.344 3942876.441, 247684.630 3943652.325,247804.201 3943957.896))'', 26917) --!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! --MAKE SURE YOU SPECIFY THE NAME OF YOUR SPATIAL TABLE --AND THE NAME OF THE SPATIAL INDEX -- IN THE sp_help_spatial_geometry_index_xml VARIABLES --!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! exec sp_help_spatial_geometry_index_xml TEST_GEOM , S1169_idx , 1, @geom, @x output SET @PFVALUE = @x.value(''(/Primary_Filter_Efficiency/text())[1]'', ''float'') SET @IFVALUE = @x.value(''(/Internal_Filter_Efficiency/text())[1]'', ''float'') SET @GRIDL1VALUE = @x.value(''(/Grid_Size_Level_1/text())[1]'', ''int'') SET @GRIDL2VALUE = @x.value(''(/Grid_Size_Level_2/text())[1]'', ''int'') SET @GRIDL3VALUE = @x.value(''(/Grid_Size_Level_3/text())[1]'', ''int'') SET @GRIDL4VALUE = @x.value(''(/Grid_Size_Level_4/text())[1]'', ''int'') SET @TPIRVALUE = @x.value(''(/Total_Primary_Index_Rows/text())[1]'', ''bigint'') SET @TPIPVALUE = @x.value(''(/Total_Primary_Index_Pages/text())[1]'', ''bigint'') SET @ANOIRPBRVALUE = @x.value(''(/Average_Number_Of_Index_Rows_Per_Base_Row/text())[1]'', ''bigint'') SET @TNOOCILFQVALUE = @x.value(''(/Total_Number_Of_ObjectCells_In_Level0_For_QuerySample/text())[1]'', ''bigint'') SET @TNOOCIL0IIVALUE = @x.value(''(/Total_Number_Of_ObjectCells_In_Level0_In_Index/text())[1]'', ''bigint'') SET @TNOOCIL4IIVALUE = @x.value(''(/Total_Number_Of_ObjectCells_In_Level4_In_Index/text())[1]'', ''bigint'') SET @TNOOCIL3FQVALUE = @x.value(''(/Total_Number_Of_ObjectCells_In_Level3_For_QuerySample/text())[1]'', ''bigint'') SET @TNOOCIL4FQVALUE = @x.value(''(/Total_Number_Of_ObjectCells_In_Level4_For_QuerySample/text())[1]'', ''bigint'') SET @TNOIOIL3FQVALUE = @x.value(''(/Total_Number_Of_Interior_ObjectCells_In_Level3_For_QuerySample/text())[1]'', ''bigint'') SET @TNOIOIL4FQVALUE = @x.value(''(/Total_Number_Of_Interior_ObjectCells_In_Level4_For_QuerySample/text())[1]'', ''bigint'') SET @ITTCNTLGPVALUE = @x.value(''(/Interior_To_Total_Cells_Normalized_To_Leaf_Grid_Percentage/text())[1]'', ''float'') SET @INTTTCNTLGPVALUE = @x.value(''(/Intersecting_To_Total_Cells_Normalized_To_Leaf_Grid_Percentage/text())[1]'', ''float'') SET @BTTCNTLGPVALUE = @x.value(''(/Border_To_Total_Cells_Normalized_To_Leaf_Grid_Percentage/text())[1]'', ''float'') SET @ACPONTLGPVALUE = @x.value(''(/Average_Cells_Per_Object_Normalized_To_Leaf_Grid/text())[1]'', ''float'') SET @AOPGVALUE = @x.value(''(/Average_Objects_PerLeaf_GridCell/text())[1]'', ''float'') SET @NORSBPFVALUE = @x.value(''(/Number_Of_Rows_Selected_By_Primary_Filter/text())[1]'', ''bigint'') SET @NORSBIFVALUE = @x.value(''(/Number_Of_Rows_Selected_By_Internal_Filter/text())[1]'', ''bigint'') SET @NOTSFICVALUE = @x.value(''(/Number_Of_Times_Secondary_Filter_Is_Called/text())[1]'', ''bigint'') SET @NOROVALUE = @x.value(''(/Number_Of_Rows_Output/text())[1]'', ''bigint'') SET @PORNBPFVALUE = @x.value(''(/Percentage_Of_Rows_NotSelected_By_Primary_Filter/text())[1]'', ''float'') SET @POPFRSBIFVALUE = @x.value(''(/Percentage_Of_Primary_Filter_Rows_Selected_By_Internal_Filter/text())[1]'', ''float'') UPDATE spat_idx_test_result SET num_cells = ' +@num_cell +', permut = ' +@permut +', g2t' +@a4 +' = ' +@time_str +', PF_EFF = @PFVALUE, IF_EFF = @IFVALUE, GRIDL1 = @GRIDL1VALUE, GRIDL2 = @GRIDL2VALUE, GRIDL3 = @GRIDL3VALUE, GRIDL4 = @GRIDL4VALUE, TPIR = @TPIRVALUE, TPIP = @TPIPVALUE, ANOIRPBR = @ANOIRPBRVALUE, TNOOCILFQ = @TNOOCILFQVALUE, TNOOCIL0II = @TNOOCIL0IIVALUE, TNOOCIL4II = @TNOOCIL4IIVALUE, TNOOCIL3FQ = @TNOOCIL3FQVALUE, TNOOCIL4FQ = @TNOOCIL4FQVALUE, TNOIOIL3FQ = @TNOIOIL3FQVALUE, TNOIOIL4FQ = @TNOIOIL4FQVALUE, ITTCNTLGP = @ITTCNTLGPVALUE, INTTTCNTLGP = @INTTTCNTLGPVALUE, BTTCNTLGP = @BTTCNTLGPVALUE, ACPONTLGP = @ACPONTLGPVALUE, AOPG = @AOPGVALUE, NORSBPF = @NORSBPFVALUE, NORSBIF = @NORSBIFVALUE, NOTSFIC = @NOTSFICVALUE, NORO = @NOROVALUE, PORNBPF = @PORNBPFVALUE, POPFRSBIF = @POPFRSBIFVALUE WHERE perm_id = ' +@perm_id ) SET @a4 = @a4 + 1 END SET @a2 = @a2 + 1 END SET @a1 = @a1 + 1 END PRINT 'Testing of ' +@tabnm +' spatial index: ' +@idxnm +' is complete!' GO
The hacking that I did involved using the xml output of the index help stored procedure to write some more descriptive results to the output in addition to query time.
The stored procedure is executed like so:
DECLARE @BOUNDING VARCHAR(MAX) SET @BOUNDING = 'GEOMETRY::STGeomFromText(''POLYGON ((226805.072 3975572.527, 318101.215 3975985.165, 317894.896 3922239.073, 225360.839 3926571.772 , 226805.072 3975572.527))'', 0)' DECLARE @QUERY VARCHAR(MAX) SET @QUERY = 'GEOMETRY::STGeomFromText(''POLYGON ((247804.201 3943957.896, 29932.568 3943963.210, 247671.344 3942876.441, 247684.630 3943652.325, 247804.201 3943957.896))'', 26917)' EXEC sp_tune_spatial_index 'TEST_GEOM', 'S1169_idx', 4096, 4096, @BOUNDING, @QUERY GO
In this example I'm only testing one Cell Size: 4096, but you could use any value range such as 8, 16.
Results can be nicely reviewed with the following:
SELECT perm_id as 'Permutation #' ,num_cells 'Cells Per Object' ,permut as 'Grids' ,g1t1 as 'ms to query entire geometry (Level 1)' ,g1t2 as 'ms to query entire geometry (Level 2)' ,g1t3 as 'ms to query entire geometry (Level 3)' ,g1t4 as 'ms to query entire geometry (Level 4)' ,g2t1 as 'ms to execute spatial query (Level 1)' ,g2t2 as 'ms to execute spatial query (Level 2)' ,g2t3 as 'ms to execute spatial query (Level 3)' ,g2t4 as 'ms to execute spatial query (Level 4)' ,PF_EFF as 'Primary Filter Efficiency' ,IF_EFF as 'Internal Filter Efficiency' ,GRIDL1 as 'Grid Size Level 1' ,GRIDL2 as 'Grid Size Level 2' ,GRIDL3 as 'Grid Size Level 3' ,GRIDL4 as 'Grid Size Level 4' ,TPIR as 'Total Primary Index Rows' ,TPIP as 'Total Primary Index Pages' ,ANOIRPBR as 'Average Number of Index Rows Per Base Row' ,TNOOCILFQ as 'Total Number of Object Cells in Level 0 For Query Sample' ,TNOOCIL3FQ as 'Total Number of Object Cells in Level 3 For Query Sample' ,TNOOCIL4FQ as 'Total Number of Object Cells in Level 4 For Query Sample' ,TNOOCIL0II as 'Total Number of Object Cells In Level 0 In Index' ,TNOOCIL4II as 'Total Number of Object Cells In Level 4 In Index' ,TNOIOIL3FQ as 'Total Number Of Interior ObjectCells In Level 3 For QuerySample' ,TNOIOIL4FQ as 'Total Number Of Interior ObjectCells In Level 4 For QuerySample' ,ITTCNTLGP as 'Interior To Total Cells Normalized To Leaf Grid Percentage' ,INTTTCNTLGP as 'Intersecting To Total Cells Normalized To Leaf Grid Percentage' ,BTTCNTLGP as 'Border To Total Cells Normalized To Leaf Grid Percentage' ,ACPONTLGP as 'Average Cells Per Object Normalized To Leaf Grid' ,AOPG as 'Average Objects PerLeaf GridCell' ,NORSBPF as 'Number Of Rows Selected By Primary Filter' ,NORSBIF as 'Number Of Rows Selected By Internal Filter' ,NOTSFIC as 'Number Of Times Secondary Filter Is Called' ,NORO as 'Number Of Rows Output' ,PORNBPF as 'Percentage Of Rows NotSelected By Primary Filter' ,POPFRSBIF as 'Percentage Of Primary Filter Rows Selected By Internal Filter' FROM spat_idx_test_result
ORDER BY PF_EFF
Permutation # | Cells Per Object | Grids | ms to query entire geometry (Level 1) | ms to query entire geometry (Level 2) | ms to query entire geometry (Level 3) | ms to query entire geometry (Level 4) | ms to execute spatial query (Level 1) | ms to execute spatial query (Level 2) | ms to execute spatial query (Level 3) | ms to execute spatial query (Level 4) | Primary Filter Efficiency | Internal Filter Efficiency | Grid Size Level 1 | Grid Size Level 2 | Grid Size Level 3 | Grid Size Level 4 | Total Primary Index Rows | Total Primary Index Pages | Average Number of Index Rows Per Base Row | Total Number of Object Cells in Level 0 For Query Sample | Total Number of Object Cells in Level 3 For Query Sample | Total Number of Object Cells in Level 4 For Query Sample | Total Number of Object Cells In Level 0 In Index | Total Number of Object Cells In Level 4 In Index | Total Number Of Interior ObjectCells In Level 3 For QuerySample | Total Number Of Interior ObjectCells In Level 4 For QuerySample | Interior To Total Cells Normalized To Leaf Grid Percentage | Intersecting To Total Cells Normalized To Leaf Grid Percentage | Border To Total Cells Normalized To Leaf Grid Percentage | Average Cells Per Object Normalized To Leaf Grid | Average Objects PerLeaf GridCell | Number Of Rows Selected By Primary Filter | Number Of Rows Selected By Internal Filter | Number Of Times Secondary Filter Is Called | Number Of Rows Output | Percentage Of Rows NotSelected By Primary Filter | Percentage Of Primary Filter Rows Selected By Internal Filter |
0 | 16 | 0 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL |
6 | 4096 | LLMH | 90 | 66 | 70 | 66 | 46 | 16 | 30 | 23 | 68.2539682539683 | 69.7674418604651 | 16 | 16 | 64 | 256 | 21278 | 66 | 10 | 1 | 110 | 3983 | 2 | 21276 | 72 | 3559 | 89.3547577203113 | 10.5699221692192 | 0.0753201104694954 | 2.0425641025641 | 0.48958071805172 | 63 | 30 | 33 | 43 | 96.7692307692308 | 47.6190476190476 |
70 | 4096 | HMHL | 156 | 136 | 130 | 146 | 50 | 33 | 36 | 33 | 68.2539682539683 | 69.7674418604651 | 256 | 64 | 256 | 16 | 79767 | 239 | 40 | 1 | 3980 | 6 | 2 | 79765 | 3559 | NULL | 0 | 0 | 0 | 0 | 0 | 63 | 30 | 33 | 43 | 96.7692307692308 | 47.6190476190476 |
71 | 4096 | HMHM | 233 | 226 | 203 | 166 | 43 | 40 | 40 | 66 | 68.2539682539683 | 69.7674418604651 | 256 | 64 | 256 | 64 | 157432 | 472 | 80 | 1 | 3980 | 5 | 2 | 157410 | 3559 | NULL | 0 | 0 | 0 | 0 | 0 | 63 | 30 | 33 | 43 | 96.7692307692308 | 47.6190476190476 |
72 | 4096 | HMHH | 376 | 310 | 263 | 266 | 53 | 63 | 73 | 56 | 68.2539682539683 | 69.7674418604651 | 256 | 64 | 256 | 256 | 306611 | 915 | 157 | 1 | 3981 | 5 | 2 | 306176 | 3559 | NULL | 0 | 0 | 0 | 0 | 0 | 63 | 30 | 33 | 43 | 96.7692307692308 | 47.6190476190476 |
52 | 4096 | MHHL | 156 | 116 | 133 | 140 | 46 | 33 | 43 | 40 | 68.2539682539683 | 69.7674418604651 | 64 | 256 | 256 | 16 | 79767 | 239 | 40 | 1 | 3980 | 6 | 2 | 79765 | 3559 | NULL | 0 | 0 | 0 | 0 | 0 | 63 | 30 | 33 | 43 | 96.7692307692308 | 47.6190476190476 |
53 | 4096 | MHHM | 243 | 216 | 210 | 186 | 43 | 43 | 43 | 33 | 68.2539682539683 | 69.7674418604651 | 64 | 256 | 256 | 64 | 157432 | 472 | 80 | 1 | 3980 | 5 | 2 | 157410 | 3559 | NULL | 0 | 0 | 0 | 0 | 0 | 63 | 30 | 33 | 43 | 96.7692307692308 | 47.6190476190476 |
54 | 4096 | MHHH | 366 | 256 | 263 | 266 | 56 | 43 | 56 | 50 | 68.2539682539683 | 69.7674418604651 | 64 | 256 | 256 | 256 | 306611 | 915 | 157 | 1 | 3981 | 5 | 2 | 306176 | 3559 | NULL | 0 | 0 | 0 | 0 | 0 | 63 | 30 | 33 | 43 | 96.7692307692308 | 47.6190476190476 |
30 | 4096 | MLLH | 86 | 63 | 70 | 66 | 40 | 26 | 30 | 20 | 68.2539682539683 | 69.7674418604651 | 64 | 16 | 16 | 256 | 21278 | 66 | 10 | 1 | 102 | 3994 | 2 | 21276 | 72 | 3429 | 85.8537806710065 | 14.07110665999 | 0.0751126690035053 | 2.04820512820513 | 0.488232348522784 | 63 | 30 | 33 | 43 | 96.7692307692308 | 47.6190476190476 |
12 | 4096 | LMLH | 83 | 73 | 63 | 63 | 43 | 23 | 26 | 20 | 70.4918032786885 | 72.0930232558139 | 16 | 64 | 16 | 256 | 21278 | 66 | 10 | 1 | 95 | 3999 | 2 | 21276 | 72 | 3331 | 83.295823955989 | 16.6291572893223 | 0.0750187546886722 | 2.05076923076923 | 0.487621905476369 | 61 | 31 | 30 | 43 | 96.8717948717949 | 50.8196721311475 |
26 | 4096 | LHHM | 156 | 140 | 143 | 140 | 50 | 40 | 40 | 30 | 78.1818181818182 | 41.8604651162791 | 16 | 256 | 256 | 64 | 79767 | 239 | 40 | 1 | 4008 | 77 | 2 | 79765 | 3576 | NULL | 0 | 0 | 0 | 0 | 0 | 55 | 18 | 37 | 43 | 97.1794871794872 | 32.7272727272727 |
27 | 4096 | LHHH | 153 | 143 | 170 | 163 | 56 | 36 | 46 | 30 | 78.1818181818182 | 41.8604651162791 | 16 | 256 | 256 | 256 | 157432 | 472 | 80 | 1 | 4013 | 72 | 2 | 157420 | 3576 | NULL | 0 | 0 | 0 | 0 | 0 | 55 | 18 | 37 | 43 | 97.1794871794872 | 32.7272727272727 |
25 | 4096 | LHHL | 116 | 86 | 83 | 80 | 43 | 36 | 40 | 33 | 78.1818181818182 | 41.8604651162791 | 16 | 256 | 256 | 16 | 40769 | 123 | 20 | 1 | 3996 | 90 | 2 | 40767 | 3576 | NULL | 99.8429483823683 | 0.155306599657976 | 0.00174501797368513 | 29.3876923076923 | 0.03402785048686 | 55 | 18 | 37 | 43 | 97.1794871794872 | 32.7272727272727 |
43 | 4096 | MMHL | 76 | 63 | 63 | 63 | 33 | 30 | 40 | 33 | 78.1818181818182 | 41.8604651162791 | 64 | 64 | 256 | 16 | 40769 | 123 | 20 | 1 | 4003 | 83 | 2 | 40767 | 3576 | 24 | 28.9156626506024 | 69.8795180722892 | 1.20481927710843 | 0.0425641025641026 | 23.4939759036145 | 55 | 18 | 37 | 43 | 97.1794871794872 | 32.7272727272727 |
44 | 4096 | MMHM | 153 | 143 | 133 | 126 | 43 | 40 | 43 | 30 | 78.1818181818182 | 41.8604651162791 | 64 | 64 | 256 | 64 | 79767 | 239 | 40 | 1 | 4008 | 77 | 2 | 79765 | 3576 | NULL | 0 | 0 | 0 | 0 | 0 | 55 | 18 | 37 | 43 | 97.1794871794872 | 32.7272727272727 |
45 | 4096 | MMHH | 233 | 223 | 223 | 176 | 43 | 40 | 50 | 30 | 78.1818181818182 | 41.8604651162791 | 64 | 64 | 256 | 256 | 157432 | 472 | 80 | 1 | 4013 | 72 | 2 | 157420 | 3576 | NULL | 0 | 0 | 0 | 0 | 0 | 55 | 18 | 37 | 43 | 97.1794871794872 | 32.7272727272727 |
39 | 4096 | MMLH | 106 | 96 | 90 | 96 | 43 | 20 | 33 | 20 | 84.3137254901961 | 74.4186046511628 | 64 | 64 | 16 | 256 | 40769 | 123 | 20 | 1 | 332 | 3749 | 2 | 40767 | 229 | 3355 | 89.4905308082155 | 9.89597225926914 | 0.613496932515337 | 1.9225641025641 | 0.520138703654308 | 51 | 32 | 19 | 43 | 97.3846153846154 | 62.7450980392157 |
33 | 4096 | MLMH | 110 | 93 | 90 | 96 | 43 | 20 | 33 | 26 | 84.3137254901961 | 74.4186046511628 | 64 | 16 | 64 | 256 | 40769 | 123 | 20 | 1 | 425 | 3669 | 2 | 40767 | 325 | 3227 | 87.9531207413464 | 11.4200054510766 | 0.626873807576996 | 1.88153846153846 | 0.531479967293541 | 51 | 32 | 19 | 43 | 97.3846153846154 | 62.7450980392157 |
79 | 4096 | HHHL | 246 | 206 | 173 | 176 | 46 | 40 | 46 | 26 | 84.3137254901961 | 74.4186046511628 | 256 | 256 | 256 | 16 | 157433 | 472 | 80 | 1 | 3667 | NULL | 2 | 157386 | 3291 | NULL | 25.0673623475421 | 74.9250207085662 | 0.00761694389168706 | 107.722051282051 | 0.0092831503679936 | 51 | 32 | 19 | 43 | 97.3846153846154 | 62.7450980392157 |
80 | 4096 | HHHM | 380 | 350 | 293 | 246 | 43 | 43 | 46 | 46 | 84.3137254901961 | 74.4186046511628 | 256 | 256 | 256 | 64 | 306612 | 915 | 157 | 1 | 3667 | NULL | 2 | 305697 | 3291 | NULL | 0 | 0 | 0 | 0 | 0 | 51 | 32 | 19 | 43 | 97.3846153846154 | 62.7450980392157 |
81 | 4096 | HHHH | 550 | 486 | 430 | 516 | 60 | 60 | 50 | 56 | 84.3137254901961 | 74.4186046511628 | 256 | 256 | 256 | 256 | 560683 | 1671 | 287 | 1 | 3667 | NULL | 2 | 556594 | 3291 | NULL | 60.2064107090026 | 39.7752950306786 | 0.0182942603187489 | 717.613333333333 | 0.0013935081102172 | 51 | 32 | 19 | 43 | 97.3846153846154 | 62.7450980392157 |
57 | 4096 | HLLH | 113 | 96 | 90 | 90 | 46 | 23 | 33 | 16 | 84.3137254901961 | 74.4186046511628 | 256 | 16 | 16 | 256 | 40769 | 123 | 20 | 1 | 331 | 3749 | 2 | 40767 | 229 | 3339 | 89.0637503334222 | 10.3227527340624 | 0.613496932515337 | 1.9225641025641 | 0.520138703654308 | 51 | 32 | 19 | 43 | 97.3846153846154 | 62.7450980392157 |
9 | 4096 | LLHH | 113 | 90 | 83 | 73 | 36 | 20 | 30 | 26 | 84.3137254901961 | 74.4186046511628 | 16 | 16 | 256 | 256 | 40769 | 123 | 20 | 1 | 430 | 3653 | 2 | 40767 | 325 | 3291 | 90.0903367095538 | 9.28004379961675 | 0.629619490829455 | 1.87333333333333 | 0.533807829181495 | 51 | 32 | 19 | 43 | 97.3846153846154 | 62.7450980392157 |
1 | 4096 | LLLL | 53 | 36 | 36 | 36 | 26 | 16 | 10 | 13 | 84.3137254901961 | 74.4186046511628 | 16 | 16 | 16 | 16 | 4230 | 15 | 2 | 1 | 6 | 358 | 2 | 4228 | 6 | 229 | 0 | 0 | 0 | 0 | 0 | 51 | 32 | 19 | 43 | 97.3846153846154 | 62.7450980392157 |
15 | 4096 | LMMH | 110 | 83 | 83 | 80 | 46 | 26 | 36 | 26 | 84.3137254901961 | 76.7441860465116 | 16 | 64 | 64 | 256 | 40769 | 123 | 20 | 1 | 403 | 3681 | 2 | 40767 | 325 | 2890 | 78.5112741102961 | 20.8638956805216 | 0.624830209182287 | 1.88769230769231 | 0.529747351263244 | 51 | 33 | 18 | 43 | 97.3846153846154 | 64.7058823529412 |
21 | 4096 | LHLH | 106 | 96 | 90 | 80 | 40 | 20 | 30 | 20 | 84.3137254901961 | 76.7441860465116 | 16 | 256 | 16 | 256 | 40769 | 123 | 20 | 1 | 313 | 3776 | 2 | 40767 | 229 | 3073 | 81.3824152542373 | 18.0084745762712 | 0.609110169491525 | 1.93641025641026 | 0.516419491525424 | 51 | 33 | 18 | 43 | 97.3846153846154 | 64.7058823529412 |
22 | 4096 | LHML | 90 | 70 | 73 | 73 | 53 | 23 | 40 | 26 | 91.4893617021277 | 93.0232558139535 | 16 | 256 | 64 | 16 | 21278 | 66 | 10 | 1 | 986 | 2342 | 2 | 21276 | 986 | 1320 | 56.3620836891546 | 43.5098206660974 | 0.128095644748079 | 1.20102564102564 | 0.832621690862511 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
23 | 4096 | LHMM | 110 | 100 | 90 | 90 | 53 | 36 | 40 | 33 | 91.4893617021277 | 76.7441860465116 | 16 | 256 | 64 | 64 | 40769 | 123 | 20 | 1 | 1142 | 2941 | 2 | 40767 | 986 | 2147 | 73.0023801428086 | 26.1475688541313 | 0.850051003060184 | 1.50820512820513 | 0.663039782386943 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
24 | 4096 | LHMH | 156 | 143 | 143 | 123 | 60 | 30 | 43 | 33 | 91.4893617021277 | 76.7441860465116 | 16 | 256 | 64 | 256 | 79767 | 239 | 40 | 1 | 1196 | 2868 | 2 | 79765 | 986 | 2161 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
16 | 4096 | LMHL | 90 | 73 | 70 | 73 | 50 | 26 | 40 | 26 | 91.4893617021277 | 93.0232558139535 | 16 | 64 | 256 | 16 | 21278 | 66 | 10 | 1 | 1370 | 2342 | 2 | 21276 | 1370 | 1320 | 56.3620836891546 | 43.5098206660974 | 0.128095644748079 | 1.20102564102564 | 0.832621690862511 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
17 | 4096 | LMHM | 103 | 96 | 83 | 73 | 46 | 26 | 33 | 26 | 91.4893617021277 | 76.7441860465116 | 16 | 64 | 256 | 64 | 40769 | 123 | 20 | 1 | 1529 | 2565 | 2 | 40767 | 1370 | 1797 | 70.0584795321637 | 29.3567251461988 | 0.584795321637427 | 1.31538461538461 | 0.760233918128655 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
18 | 4096 | LMHH | 156 | 146 | 120 | 103 | 50 | 33 | 43 | 30 | 91.4893617021277 | 76.7441860465116 | 16 | 64 | 256 | 256 | 79767 | 239 | 40 | 1 | 1583 | 2512 | 2 | 79765 | 1370 | 1854 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
19 | 4096 | LHLL | 76 | 56 | 56 | 53 | 40 | 16 | 33 | 23 | 91.4893617021277 | 76.7441860465116 | 16 | 256 | 16 | 16 | 11543 | 37 | 5 | 1 | 229 | 932 | 2 | 11541 | 229 | 420 | 45.0643776824034 | 54.7210300429185 | 0.214592274678112 | 0.477948717948718 | 2.09227467811159 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
20 | 4096 | LHLM | 80 | 70 | 70 | 70 | 46 | 23 | 30 | 26 | 91.4893617021277 | 93.0232558139535 | 16 | 256 | 16 | 64 | 21278 | 66 | 10 | 1 | 229 | 3462 | 2 | 21276 | 229 | 2440 | 70.4794916233391 | 29.4338532640092 | 0.0866551126516464 | 1.77538461538461 | 0.563258232235702 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
2 | 4096 | LLLM | 60 | 40 | 36 | 40 | 36 | 20 | 26 | 26 | 91.4893617021277 | 76.7441860465116 | 16 | 16 | 16 | 64 | 6617 | 22 | 3 | 1 | 6 | 1241 | 2 | 6615 | 6 | 986 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
3 | 4096 | LLLH | 73 | 56 | 56 | 60 | 50 | 20 | 30 | 23 | 91.4893617021277 | 46.5116279069767 | 16 | 16 | 16 | 256 | 11543 | 37 | 5 | 1 | 9 | 4052 | 2 | 11541 | 6 | 3592 | 88.6475814412636 | 11.1056268509378 | 0.246791707798618 | 2.07794871794872 | 0.481243830207305 | 47 | 20 | 27 | 43 | 97.5897435897436 | 42.5531914893617 |
4 | 4096 | LLML | 56 | 40 | 43 | 40 | 33 | 16 | 20 | 16 | 91.4893617021277 | 76.7441860465116 | 16 | 16 | 64 | 16 | 6617 | 22 | 3 | 1 | 72 | 473 | 2 | 6615 | 72 | 218 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
5 | 4096 | LLMM | 73 | 56 | 60 | 56 | 43 | 30 | 30 | 23 | 91.4893617021277 | 76.7441860465116 | 16 | 16 | 64 | 64 | 11543 | 37 | 5 | 1 | 72 | 1524 | 2 | 11541 | 72 | 1012 | 66.4041994750656 | 33.4645669291339 | 0.131233595800525 | 0.781538461538462 | 1.27952755905512 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
10 | 4096 | LMLL | 63 | 40 | 36 | 36 | 26 | 20 | 20 | 16 | 91.4893617021277 | 76.7441860465116 | 16 | 64 | 16 | 16 | 6617 | 22 | 3 | 1 | 72 | 473 | 2 | 6615 | 72 | 218 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
11 | 4096 | LMLM | 73 | 56 | 53 | 53 | 40 | 30 | 30 | 16 | 91.4893617021277 | 76.7441860465116 | 16 | 64 | 16 | 64 | 11543 | 37 | 5 | 1 | 72 | 1524 | 2 | 11541 | 72 | 1012 | 66.4041994750656 | 33.4645669291339 | 0.131233595800525 | 0.781538461538462 | 1.27952755905512 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
7 | 4096 | LLHL | 73 | 60 | 56 | 56 | 40 | 23 | 33 | 20 | 91.4893617021277 | 76.7441860465116 | 16 | 16 | 256 | 16 | 11543 | 37 | 5 | 1 | 325 | 932 | 2 | 11541 | 325 | 420 | 45.0643776824034 | 54.7210300429185 | 0.214592274678112 | 0.477948717948718 | 2.09227467811159 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
8 | 4096 | LLHM | 90 | 66 | 73 | 66 | 40 | 23 | 30 | 23 | 91.4893617021277 | 93.0232558139535 | 16 | 16 | 256 | 64 | 21278 | 66 | 10 | 1 | 325 | 3462 | 2 | 21276 | 325 | 2440 | 70.4794916233391 | 29.4338532640092 | 0.0866551126516464 | 1.77538461538461 | 0.563258232235702 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
58 | 4096 | HLML | 93 | 76 | 70 | 76 | 53 | 26 | 40 | 30 | 91.4893617021277 | 93.0232558139535 | 256 | 16 | 64 | 16 | 21278 | 66 | 10 | 1 | 986 | 2342 | 2 | 21276 | 986 | 1320 | 56.3620836891546 | 43.5098206660974 | 0.128095644748079 | 1.20102564102564 | 0.832621690862511 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
59 | 4096 | HLMM | 116 | 93 | 103 | 93 | 56 | 26 | 43 | 26 | 91.4893617021277 | 76.7441860465116 | 256 | 16 | 64 | 64 | 40769 | 123 | 20 | 1 | 1158 | 2931 | 2 | 40767 | 986 | 2272 | 77.5162060730126 | 21.9720232002729 | 0.511770726714432 | 1.50307692307692 | 0.665301944728761 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
60 | 4096 | HLMH | 156 | 143 | 143 | 143 | 60 | 36 | 46 | 30 | 91.4893617021277 | 76.7441860465116 | 256 | 16 | 64 | 256 | 79767 | 239 | 40 | 1 | 1216 | 2869 | 2 | 79765 | 986 | 2486 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
61 | 4096 | HLHL | 116 | 100 | 96 | 100 | 53 | 33 | 50 | 26 | 91.4893617021277 | 46.5116279069767 | 256 | 16 | 256 | 16 | 40769 | 123 | 20 | 1 | 4046 | 41 | 2 | 40767 | 3592 | 24 | 58.5365853658536 | 39.0243902439024 | 2.4390243902439 | 0.021025641025641 | 47.5609756097561 | 47 | 20 | 27 | 43 | 97.5897435897436 | 42.5531914893617 |
62 | 4096 | HLHM | 150 | 140 | 140 | 143 | 56 | 33 | 43 | 26 | 91.4893617021277 | 46.5116279069767 | 256 | 16 | 256 | 64 | 79767 | 239 | 40 | 1 | 4044 | 43 | 2 | 79765 | 3592 | NULL | 0 | 0 | 0 | 0 | 0 | 47 | 20 | 27 | 43 | 97.5897435897436 | 42.5531914893617 |
63 | 4096 | HLHH | 156 | 146 | 146 | 146 | 36 | 33 | 46 | 33 | 91.4893617021277 | 46.5116279069767 | 256 | 16 | 256 | 256 | 157432 | 472 | 80 | 1 | 4047 | 35 | 2 | 157420 | 3592 | NULL | 0 | 0 | 0 | 0 | 0 | 47 | 20 | 27 | 43 | 97.5897435897436 | 42.5531914893617 |
64 | 4096 | HMLL | 63 | 56 | 56 | 53 | 33 | 20 | 36 | 30 | 91.4893617021277 | 93.0232558139535 | 256 | 64 | 16 | 16 | 21278 | 66 | 10 | 1 | 218 | 2342 | 2 | 21276 | 218 | 1320 | 56.3620836891546 | 43.5098206660974 | 0.128095644748079 | 1.20102564102564 | 0.832621690862511 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
65 | 4096 | HMLM | 116 | 100 | 86 | 73 | 40 | 30 | 33 | 23 | 91.4893617021277 | 76.7441860465116 | 256 | 64 | 16 | 64 | 40769 | 123 | 20 | 1 | 376 | 3648 | 2 | 40767 | 218 | 2876 | 78.8377192982456 | 20.7510964912281 | 0.411184210526316 | 1.87076923076923 | 0.534539473684211 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
66 | 4096 | HMLH | 156 | 116 | 106 | 113 | 43 | 36 | 40 | 23 | 91.4893617021277 | 76.7441860465116 | 256 | 64 | 16 | 256 | 79767 | 239 | 40 | 1 | 442 | 3581 | 2 | 79765 | 218 | 3089 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
67 | 4096 | HMML | 113 | 103 | 100 | 103 | 53 | 33 | 40 | 33 | 91.4893617021277 | 76.7441860465116 | 256 | 64 | 64 | 16 | 40769 | 123 | 20 | 1 | 1305 | 2719 | 2 | 40767 | 1012 | 1855 | 68.2236116219198 | 31.5189407870541 | 0.257447591026112 | 1.39435897435897 | 0.717175432144171 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
68 | 4096 | HMMM | 153 | 123 | 106 | 143 | 53 | 36 | 43 | 26 | 91.4893617021277 | 76.7441860465116 | 256 | 64 | 64 | 64 | 79767 | 239 | 40 | 1 | 1445 | 2579 | 2 | 79765 | 1012 | 1964 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
69 | 4096 | HMMH | 236 | 190 | 163 | 146 | 43 | 40 | 46 | 40 | 91.4893617021277 | 76.7441860465116 | 256 | 64 | 64 | 256 | 157432 | 472 | 80 | 1 | 1504 | 2518 | 2 | 157420 | 1012 | 2231 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
73 | 4096 | HHLL | 113 | 93 | 90 | 83 | 50 | 36 | 63 | 36 | 91.4893617021277 | 76.7441860465116 | 256 | 256 | 16 | 16 | 40769 | 123 | 20 | 1 | 692 | 3079 | 2 | 40767 | 420 | 2131 | 69.2107827216629 | 30.5618707372524 | 0.227346541084768 | 1.57897435897436 | 0.633322507307567 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
74 | 4096 | HHLM | 120 | 96 | 90 | 93 | 40 | 36 | 43 | 33 | 91.4893617021277 | 76.7441860465116 | 256 | 256 | 16 | 64 | 79767 | 239 | 40 | 1 | 852 | 2918 | 2 | 79765 | 420 | 2300 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
75 | 4096 | HHLH | 236 | 220 | 210 | 210 | 53 | 46 | 53 | 30 | 91.4893617021277 | 76.7441860465116 | 256 | 256 | 16 | 256 | 157432 | 472 | 80 | 1 | 909 | 2862 | 2 | 157419 | 420 | 2512 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
76 | 4096 | HHML | 170 | 146 | 146 | 143 | 50 | 30 | 33 | 33 | 91.4893617021277 | 93.0232558139535 | 256 | 256 | 64 | 16 | 79767 | 239 | 40 | 1 | 3433 | 338 | 2 | 79765 | 2440 | 229 | 64.6892655367232 | 30.7909604519774 | 4.51977401129944 | 0.181538461538462 | 5.50847457627119 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
77 | 4096 | HHMM | 236 | 220 | 220 | 200 | 56 | 36 | 36 | 36 | 91.4893617021277 | 93.0232558139535 | 256 | 256 | 64 | 64 | 157432 | 472 | 80 | 1 | 3448 | 323 | 2 | 157410 | 2440 | 224 | 57.8811369509044 | 25.5813953488372 | 16.5374677002584 | 0.198461538461538 | 5.03875968992248 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
78 | 4096 | HHMH | 360 | 353 | 336 | 353 | 60 | 40 | 50 | 33 | 91.4893617021277 | 93.0232558139535 | 256 | 256 | 64 | 256 | 306611 | 915 | 157 | 1 | 3456 | 314 | 2 | 306171 | 2440 | 256 | 0 | 0 | 0 | 0 | 0 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
13 | 4096 | LMML | 66 | 60 | 56 | 50 | 43 | 26 | 30 | 23 | 91.4893617021277 | 76.7441860465116 | 16 | 64 | 64 | 16 | 11543 | 37 | 5 | 1 | 325 | 932 | 2 | 11541 | 325 | 420 | 45.0643776824034 | 54.7210300429185 | 0.214592274678112 | 0.477948717948718 | 2.09227467811159 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
14 | 4096 | LMMM | 86 | 73 | 66 | 66 | 43 | 30 | 33 | 23 | 91.4893617021277 | 93.0232558139535 | 16 | 64 | 64 | 64 | 21278 | 66 | 10 | 1 | 325 | 3462 | 2 | 21276 | 325 | 2440 | 70.4794916233391 | 29.4338532640092 | 0.0866551126516464 | 1.77538461538461 | 0.563258232235702 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
55 | 4096 | HLLL | 76 | 56 | 50 | 60 | 43 | 26 | 30 | 26 | 91.4893617021277 | 76.7441860465116 | 256 | 16 | 16 | 16 | 11543 | 37 | 5 | 1 | 229 | 932 | 2 | 11541 | 229 | 420 | 45.0643776824034 | 54.7210300429185 | 0.214592274678112 | 0.477948717948718 | 2.09227467811159 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
56 | 4096 | HLLM | 90 | 73 | 66 | 63 | 43 | 26 | 30 | 16 | 91.4893617021277 | 93.0232558139535 | 256 | 16 | 16 | 64 | 21278 | 66 | 10 | 1 | 229 | 3462 | 2 | 21276 | 229 | 2440 | 70.4794916233391 | 29.4338532640092 | 0.0866551126516464 | 1.77538461538461 | 0.563258232235702 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
34 | 4096 | MLHL | 90 | 70 | 76 | 70 | 53 | 33 | 33 | 23 | 91.4893617021277 | 93.0232558139535 | 64 | 16 | 256 | 16 | 21278 | 66 | 10 | 1 | 1370 | 2342 | 2 | 21276 | 1370 | 1320 | 56.3620836891546 | 43.5098206660974 | 0.128095644748079 | 1.20102564102564 | 0.832621690862511 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
35 | 4096 | MLHM | 106 | 103 | 93 | 83 | 43 | 33 | 40 | 33 | 91.4893617021277 | 76.7441860465116 | 64 | 16 | 256 | 64 | 40769 | 123 | 20 | 1 | 1548 | 2547 | 2 | 40767 | 1370 | 1936 | 76.010993325481 | 23.4000785237534 | 0.588928150765607 | 1.30615384615385 | 0.765606595995289 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
36 | 4096 | MLHH | 153 | 143 | 143 | 140 | 56 | 36 | 36 | 30 | 91.4893617021277 | 76.7441860465116 | 64 | 16 | 256 | 256 | 79767 | 239 | 40 | 1 | 1597 | 2480 | 2 | 79765 | 1370 | 2049 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
37 | 4096 | MMLL | 70 | 56 | 53 | 46 | 40 | 23 | 30 | 26 | 91.4893617021277 | 76.7441860465116 | 64 | 64 | 16 | 16 | 11543 | 37 | 5 | 1 | 229 | 932 | 2 | 11541 | 229 | 420 | 45.0643776824034 | 54.7210300429185 | 0.214592274678112 | 0.477948717948718 | 2.09227467811159 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
38 | 4096 | MMLM | 86 | 63 | 60 | 56 | 30 | 20 | 33 | 20 | 91.4893617021277 | 93.0232558139535 | 64 | 64 | 16 | 64 | 21278 | 66 | 10 | 1 | 229 | 3462 | 2 | 21276 | 229 | 2440 | 70.4794916233391 | 29.4338532640092 | 0.0866551126516464 | 1.77538461538461 | 0.563258232235702 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
28 | 4096 | MLLL | 56 | 40 | 40 | 36 | 26 | 20 | 20 | 13 | 91.4893617021277 | 76.7441860465116 | 64 | 16 | 16 | 16 | 6617 | 22 | 3 | 1 | 72 | 473 | 2 | 6615 | 72 | 218 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
29 | 4096 | MLLM | 76 | 60 | 56 | 56 | 43 | 16 | 30 | 20 | 91.4893617021277 | 76.7441860465116 | 64 | 16 | 16 | 64 | 11543 | 37 | 5 | 1 | 72 | 1524 | 2 | 11541 | 72 | 1012 | 66.4041994750656 | 33.4645669291339 | 0.131233595800525 | 0.781538461538462 | 1.27952755905512 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
40 | 4096 | MMML | 86 | 76 | 83 | 63 | 60 | 30 | 40 | 30 | 91.4893617021277 | 93.0232558139535 | 64 | 64 | 64 | 16 | 21278 | 66 | 10 | 1 | 986 | 2342 | 2 | 21276 | 986 | 1320 | 56.3620836891546 | 43.5098206660974 | 0.128095644748079 | 1.20102564102564 | 0.832621690862511 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
41 | 4096 | MMMM | 116 | 83 | 76 | 70 | 46 | 30 | 40 | 33 | 91.4893617021277 | 76.7441860465116 | 64 | 64 | 64 | 64 | 40769 | 123 | 20 | 1 | 1175 | 2912 | 2 | 40767 | 986 | 2388 | 82.0054945054945 | 17.4793956043956 | 0.51510989010989 | 1.49333333333333 | 0.669642857142857 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
42 | 4096 | MMMH | 163 | 143 | 143 | 133 | 50 | 36 | 43 | 33 | 91.4893617021277 | 76.7441860465116 | 64 | 64 | 64 | 256 | 79767 | 239 | 40 | 1 | 1214 | 2869 | 2 | 79765 | 986 | 2454 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
31 | 4096 | MLML | 73 | 56 | 60 | 50 | 43 | 23 | 33 | 20 | 91.4893617021277 | 76.7441860465116 | 64 | 16 | 64 | 16 | 11543 | 37 | 5 | 1 | 325 | 932 | 2 | 11541 | 325 | 420 | 45.0643776824034 | 54.7210300429185 | 0.214592274678112 | 0.477948717948718 | 2.09227467811159 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
32 | 4096 | MLMM | 86 | 63 | 73 | 63 | 40 | 16 | 33 | 20 | 91.4893617021277 | 93.0232558139535 | 64 | 16 | 64 | 64 | 21278 | 66 | 10 | 1 | 325 | 3462 | 2 | 21276 | 325 | 2440 | 70.4794916233391 | 29.4338532640092 | 0.0866551126516464 | 1.77538461538461 | 0.563258232235702 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
46 | 4096 | MHLL | 93 | 76 | 70 | 63 | 40 | 33 | 33 | 36 | 91.4893617021277 | 93.0232558139535 | 64 | 256 | 16 | 16 | 21278 | 66 | 10 | 1 | 218 | 2342 | 2 | 21276 | 218 | 1320 | 56.3620836891546 | 43.5098206660974 | 0.128095644748079 | 1.20102564102564 | 0.832621690862511 | 47 | 40 | 7 | 43 | 97.5897435897436 | 85.1063829787234 |
47 | 4096 | MHLM | 110 | 96 | 90 | 100 | 46 | 20 | 36 | 33 | 91.4893617021277 | 76.7441860465116 | 64 | 256 | 16 | 64 | 40769 | 123 | 20 | 1 | 383 | 3640 | 2 | 40767 | 218 | 2927 | 80.4120879120879 | 19.1758241758242 | 0.412087912087912 | 1.86666666666667 | 0.535714285714286 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
48 | 4096 | MHLH | 163 | 133 | 140 | 120 | 50 | 33 | 40 | 33 | 91.4893617021277 | 76.7441860465116 | 64 | 256 | 16 | 256 | 79767 | 239 | 40 | 1 | 442 | 3581 | 2 | 79765 | 218 | 3089 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
49 | 4096 | MHML | 116 | 86 | 93 | 100 | 50 | 30 | 36 | 26 | 91.4893617021277 | 76.7441860465116 | 64 | 256 | 64 | 16 | 40769 | 123 | 20 | 1 | 1305 | 2719 | 2 | 40767 | 1012 | 1855 | 68.2236116219198 | 31.5189407870541 | 0.257447591026112 | 1.39435897435897 | 0.717175432144171 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
50 | 4096 | MHMM | 156 | 120 | 133 | 116 | 43 | 40 | 43 | 40 | 91.4893617021277 | 76.7441860465116 | 64 | 256 | 64 | 64 | 79767 | 239 | 40 | 1 | 1436 | 2588 | 2 | 79765 | 1012 | 1894 | 0 | 0 | 0 | 0 | 0 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
51 | 4096 | MHMH | 233 | 223 | 180 | 220 | 63 | 30 | 43 | 26 | 91.4893617021277 | 76.7441860465116 | 64 | 256 | 64 | 256 | 157432 | 472 | 80 | 1 | 1494 | 2530 | 2 | 157420 | 1012 | 2084 | 82.3715415019763 | 16.5612648221344 | 1.06719367588933 | 1.2974358974359 | 0.770750988142292 | 47 | 33 | 14 | 43 | 97.5897435897436 | 70.2127659574468 |
This post doesn't even scratch the surface of Spatial Index Tuning. For example, if you're using SQL 2012, you could set the index to Auto Grid, which gives you 8 Cell Levels and supposedly is a good marriage for ArcGIS. You also want to look at other performance factors such as Internal Filter Efficiency. There's a lot of Witch Magic and Snake Oil Medicine to Spatial Index Tuning. Hope this blog post gets you started in the right direction!
You must be a registered user to add a comment. If you've already registered, sign in. Otherwise, register and sign in.