 Home
 Products
 Integration
 Tutorial
 Barcode FAQ
 Purchase
 Company
javascript code 39 barcode generator CHOOSING THE RIGHT NUMBER OF BUCKETS in Java
CHOOSING THE RIGHT NUMBER OF BUCKETS Code 3/9 Encoder In Java Using Barcode creation for Java Control to generate, create Code39 image in Java applications. www.OnBarcode.comReading Code39 In Java Using Barcode decoder for Java Control to read, scan read, scan image in Java applications. www.OnBarcode.comRecall that 254 buckets is (currently) the maximum number of buckets you can request for a histogram. The histogram will be a frequency histogram when the number of buckets exceeds the number of different values. If a histogram on a column is going to be beneficial, you may as well ask for the maximum bucket count as a first guess at the best number of buckets the marginal cost of the extra buckets (the default is 75) is not significant for the potential benefit you could gain from the extra precision. Encoding EAN / UCC  14 In Java Using Barcode maker for Java Control to generate, create EAN / UCC  14 image in Java applications. www.OnBarcode.comCreate PDF 417 In Java Using Barcode drawer for Java Control to generate, create PDF417 2d barcode image in Java applications. www.OnBarcode.comSince I had only 100 different values in the columns, the histograms with 254 buckets actually collapsed to become highprecision frequency histograms with 100 endpoints and an exact picture of the current data content so the optimizer was able to make very good use of them, even in the join. The histograms with 85 buckets were the more common height balanced histograms, and the critical feature was that one of them (in fact the one at the t2 end of the join) did show a popular value. It seems that if You are running 9i or 10g, And you have histograms at both ends of an equality join, And at least one histogram either is a frequency histogram or shows a popular value, then the optimizer has some method (somehow comparing the histogram data to estimate the number of rows and distinct values in each table in the overlap) that makes it possible to allow for joins where there is only a partial overlap in the ranges of values in the columns being joined. Don t take this as a directive to build histograms all over the place, though. It is useful to know, however, so that you can test the effects, when you find those few critical pieces of SQL where you can see a join cardinality going badly wrong. Creating Quick Response Code In Java Using Barcode drawer for Java Control to generate, create QR Code 2d barcode image in Java applications. www.OnBarcode.comUPCA Printer In Java Using Barcode generator for Java Control to generate, create UPCA Supplement 2 image in Java applications. www.OnBarcode.comCHAPTER 10 JOIN CARDINALITY
Drawing Matrix Barcode In Java Using Barcode drawer for Java Control to generate, create 2D image in Java applications. www.OnBarcode.comEAN8 Generation In Java Using Barcode printer for Java Control to generate, create EAN8 Supplement 5 AddOn image in Java applications. www.OnBarcode.comFREQUENCY HISTOGRAMS AND DBMS_STATS
Encode Code 39 In Visual Studio .NET Using Barcode drawer for ASP.NET Control to generate, create Code39 image in ASP.NET applications. www.OnBarcode.comCode 39 Full ASCII Generation In Java Using Barcode generation for Java Control to generate, create Code 39 Extended image in Java applications. www.OnBarcode.comThere is a problem getting a frequency histogram out of the dbms_stats package. I have examples of data sets with only 100 distinct values, but the SQL used by Oracle in 9i and 10g (until 10.2) to generate the histogram failed to build a frequency histogram until I requested 134 buckets in the baseline test. Making Barcode In None Using Barcode creator for Software Control to generate, create Barcode image in Software applications. www.OnBarcode.comScan Barcode In Java Using Barcode decoder for Java Control to read, scan read, scan image in Java applications. www.OnBarcode.comThere are a couple of side issues to consider. First, 8i also takes advantage of histograms in this situation, but the calculations used must be different because the results are much less accurate unless the histogram is the perfect frequency distribution histogram. Table 103, for example, shows the results you get from 8i when using the same 85bucket histograms as we did previously for 9i and 10g. Data Matrix Creation In None Using Barcode drawer for Software Control to generate, create Data Matrix 2d barcode image in Software applications. www.OnBarcode.comPDF417 Scanner In C# Using Barcode decoder for Visual Studio .NET Control to read, scan read, scan image in .NET framework applications. www.OnBarcode.comTable 103. Histograms in 8i Give Different Join Arithmetic
QR Code JIS X 0510 Creation In None Using Barcode creator for Word Control to generate, create Denso QR Bar Code image in Office Word applications. www.OnBarcode.comPrint European Article Number 13 In ObjectiveC Using Barcode printer for iPhone Control to generate, create EAN 13 image in iPhone applications. www.OnBarcode.comt1.join1 Low Value
Making ANSI/AIM Code 39 In VS .NET Using Barcode generator for .NET Control to generate, create Code39 image in VS .NET applications. www.OnBarcode.comCreating Matrix In VB.NET Using Barcode printer for .NET Control to generate, create 2D Barcode image in .NET applications. www.OnBarcode.com 100 50 25 10 0 25 50 75 99 100 Code 128 Maker In None Using Barcode generation for Microsoft Word Control to generate, create Code128 image in Word applications. www.OnBarcode.comRead Data Matrix In .NET Framework Using Barcode scanner for .NET framework Control to read, scan read, scan image in .NET applications. www.OnBarcode.comT1.join1 High Value
1 49 74 89 99 124 149 174 198 199 Computed Cardinality
1,000,000 147,201 350,499 497618 616,242 447,791 328,109 167,392 41,034 1,000,000 Actual Rows
0 486,318 737,270 895,925 999,920 758,631 513,404 262,170 10,560 0 The other issue is the problem of finding a histogram definition that just happens to work if you can t get a frequency distribution histogram. Basically, it is a question of choosing the right number of buckets to make a popular value visible if there is such a value. The optimizer seems to check for popular values by comparing the number of buckets defined against the number of endpoints stored. If you check view user_tab_histograms for a specific column, then the maximum value for column endpoint_number (assuming you haven t switched from a height balanced histogram to a frequency distribution histogram) will be one less than the number of rows stored if there are no popular values. To show how awkward it can be to find the right number of buckets for a histogram, look at Table 104, which was generated from the data used for the tests in join_card_06.sql. It lists a range of bucket counts and shows whether or not each bucket count managed to identify a popular value remember, all I am doing in this test is changing the number of buckets in the

