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Strategy 3 for calculating selectivity/cardinality: After that brief digression, we can investigate the issue of range scans There are many possible variants on the theme, of course so we will stick with just two indicative cases Since the data set I have been using is a fairly odd one, I have created another data set for these tests, to make sure that the results showed very clearly what Oracle is doing The script is hist_selsql in the online code suite The script generates 10,000 rows using a scaled normal distribution centered on the value 3,000 ranging from 5,000 to 11,000 Superimposed on this distribution, I have 500 rows each of the values 500, 1,000, 1,500, and so on up to 10,000 a list of 20 popular values.

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R% r3 = *r1; // A gc-lvalue r3 is assigned to the gc-rvalue *r1. } Compiling Listing 4-17 gives the following error: Microsoft (R) C/C++ Optimizing Compiler Version 14.00.50727.42 for Microsoft (R) .NET Framework version 2.00.50727.42 Copyright (C) Microsoft Corporation. All rights reserved. gc_lvalues.cpp gc_lvalues.cpp(32) : error C2440: 'initializing' : cannot convert from 'int' to 'int &' An object from the gc heap (member of a managed class) cannot be converted to a native reference

When the call comes into your BlackBerry, you should hear an audible beep in the headset. Just press the Multi-function button on your headset to answer the call. Press the Multi- function button when the call ends to disconnect.

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After analyzing this table with 250 buckets (80 rows per bucket), I get a histogram that shows the spikes from my 20 popular values The number of distinct values is 5,626 and the column density is 0000119361 (a convincing drop from 1 / 5,626 = 0000177746) My first test case is a range scan across buckets with no popular values: n1 between 100 and 200 If we check the histogram, we find that the required values fall across three buckets with endpoints 17, 117, and 251 ENDPOINT_NUMBER ENDPOINT_VALUE --------------- -------------8 -120 9 17 10 117 11 251 12 357 So we apply the standard formula bearing in mind that we have to break our required range across two separate buckets so that we examine ranges 100 117 and 117 200:.

When a phone call comes into your BlackBerry, press the Menu key. Scroll and then click to Activate (your Bluetooth headset name) and the call will be sent to the selected headset. In this image, the headset name is Jawbone.

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Selectivity = (required range) / (high value - low value) + 2 * density = (200 117)/(251-117) + (117-100)/(117-17) + 2 * 0.000177746 = 0.619403 + 0.17 + .000355486 = 0.789047508 Cardinality = selectivity * number of rows IN A BUCKET = 0.789047508 * 80 = 63.1238 Sure enough, when we run the query with autotrace, we see the following: Execution Plan (9.2.0.6 autotrace) ---------------------------------------------------------0 SELECT STATEMENT Optimizer=ALL_ROWS (Cost=60 Card=63 Bytes=945) 1 0 TABLE ACCESS (FULL) OF 'T1' (Cost=60 Card=63 Bytes=945) The second test case is, of course, a range scan across buckets with a popular value: n1 between 400 and 600. (One of my spikes was at n1 = 500.) We need to check up on a little section from the histogram that will be relevant: ENDPOINT_NUMBER ENDPOINT_VALUE --------------- -------------12 357 13 450 19 500 20 520 21 598 22 670

There is one interesting and useful variation on how you can hold references to objects that you ll want to know about: auto_handle, which is used for managed types that you want treated like automatic variables that are not created in the function, but rather come from the result of a function call.

There are several options available to you from the Bluetooth menu. Learn these commands to be able to take full advantage of Bluetooth wireless technology on your BlackBerry.

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