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A cost-based optimizer can go further Suppose the system catalog contains three additional pieces of information: (1) that there are 100 rows in Table1, (2) that there are two pages in Table1, and (3) that the value 55 appears 0 times in the index for column2 Those facts change everything The equals operation will match on 60% of the rows, so it's not a narrow search And the whole table can be scanned using two page reads, whereas an index lookup would take three page reads (one to lookup in the index, two more to fetch the data later) Therefore the cost-based optimizer makes a different plan: find matching rows using a table scan Notice that the cost-based optimizer is using volatile data (the row and column values that have been inserted) and an override (that the contents are more important than the fixed assumptions) In other words, a cost-based optimizer is a rule-based optimizer that has additional, volatile information available to it so that it can override the fixed assumptions that would otherwise govern its decisions The terminology causes an impression that one optimizer type is based on rules while the other is based on cost That's unfortunate because both optimizer types use rules and both optimizer types have the goal of calculating cost The reality is that cost-based is an extension of rule-based, and a better term would have been something like "rule-based++" Most vendors claim that their DBMSs have cost-based optimizers, as you can see from Table 17-1 The claims don't mean much by themselves What's important is whether the optimizer estimates cost correctly and how it acts on the estimate In this chapter, we'll look at the actions DBMSs take to fulfill their claims Table 17-1 Cost-Based Optimizers "Explains" the Access "Updates" Statistics for the Plan Optimizer EXPLAIN RUNSTATS SET EXPLAIN UPDATE STATISTICS EXECUTE QEP optimizedb utility SELECT PLAN SET STATISTICS EXPLAIN UPDATE STATISTICS EXPLAIN ANALYZE TABLE EXPLAIN PLAN FOR ANALYZE SET SHOWPLAN ON UPDATE STATISTICS.



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, listDataSource, "Length"); Again, this technique displays only a ingle item at a time, as shown in Figure 1310.Although arrays and other kinds of list data sources are useful, the most popular list data source s the data set You can bind to columns in a table from a data set in two ways: // Fill the data set customersAdapterFill(. Barcode Generator In Java Using Barcode printer for .Related: 

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If the difference score is less than the value listed in he table, then the difference is not uncommon. For example, if the mean of all four Indexes is 95.5 and the VCI standard score is 108, then the difference score for VCI is 12.5 (i.e., 108 95.5 = 12.5). A 13-point difference between the VCI and the mean of all Indexes is needed to be considered uncommon using the 10% base rate criterion. Thus, the difference score of 12.5 for VCI is common in the normal population. The values provided in this table are based on Longman s (2004) formula-based estimates for the overall WAIS-III standardization sample (ages 16 89). To properly interpret the person s profile using the interpretive system described in this Appendix, it is important for examiners to understand CHC theory in depth, especially the Broad Abilities and Narrow Abilities that orm the essence of CHC theory. Some of these abilities were mentioned briefly in the discussions of Steps 1 through 5 of this system, and several others are described in. rdlc reports net pdf417 2d barcode maker tomake pdf .Related: Generate EAN-8 .NET , C# Interleaved 2 of 5 Generating , Print ISBN Java

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A difference between the Controller_impl class we show in Section 10112 and this example is that we use an STL set, and not a map, as the m_assets data member This is because the Active Object Map of our POA stores the Thermometer_impl * servant pointers, so we have no need to keep a separate map that duplicates that storage Instead, m_assets stores only asset numbers The list implementation iterates over the set of asset numbers For each asset number, we must create an object reference for the device it represents To do this, we first convert the asset number to a string using an ostrstream, and then we convert the resulting string to an ObjectId using the string_to_ObjectId helper function supplied in the PortableServer namespace (this is a stand-alone function that converts strings to ObjectIds) In addition to the ObjectId, we need the repository ID for the most derived interface our new object will support To determine the correct repository ID, we use the asset number to read the model type directly from the device using the ICP_get device access function If the model type indicates that the device is a thermometer, we make the repos_id variable point to the repository ID for the Thermometer interface; otherwise, we make it point to the ID for the Thermostat interface We pass the oid and the repos_id arguments to create_reference_with_id to create the object reference for the device Because the return value of create_reference_with_id s a reference of type CORBA::Object, though, we narrow it to the CCS::Thermometer type before we assign it to our return sequence After we finish iterating over the m_assets set, we return the sequence of Thermometer references This implementation of list certainly works as desired Moreover, the fact that we do not need to create any servants to return object references for all our devices clearly illustrates that the life cycle of a CORBA object is completely independent of the life cycle of any servant used to incarnate it However, our list implementation contains a few assumptions that have some interesting side effects These side effects are related to the interface types of the objects and to the eventual activation of the objects.

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in exactly the same order, before and after the elimination; hence, the execution time cannot change The only bene t of rescheduling is a better estimation of the execution time with a more accurate schedule length Note the difference from Theorem 51 for classic scheduling, which states that the rescheduling of any schedule with a list scheduling algorithm results in a schedule at least as short as the original schedule There, it suf ces to schedule the nodes in their start time order of the original schedule Under the involvement contention model, the edge order on the links (Sections 741 and 751) as well as on the processors (Section 821, see also later) is relevant for the schedule length Generally, it is therefore necessary to repeat the scheduling with the same heuristic employed for the original schedule to ensure the exact same scheduling order of the nodes and edges Otherwise, the schedule length might increase Inserting into Gaps The insertion technique can be applied to use the emerging gaps during the scheduling This has the advantage that scheduling decisions might be different when a node or an edge can be inserted into a gap and therefore start earlier Note that use of the insertion technique in a straightforward manner is only possible because the causality Condition 81 for involvement scheduling gives the freedom of the node and edge order (Section 821) Inserting a node or an edge into a gap is very likely to separate edges from their origin or destination nodes, as, for example, in Figure 88 Scheduling Order of Edges As in contention scheduling (Sections 741 and 751), the order in which the edges are scheduled is relevant and might lead to different schedule lengths Here, the scheduling of the edges is divided into the scheduling of the entering edges on the links and the destination processors and the leaving edges provisionally on the source processors Scheduling the entering edges is very similar to the scheduling under the contention model and the same considerations apply to their order (Sections 741 and 751) A natural order of the leaving edges is the scheduling order of their destination nodes, as it follows the same rational as the minimization of the node s start and nish times (Section 51) Of course, the ordering of the edges slightly increases the complexity of a scheduling algorithm It is very important for most algorithms that the scheduling order of the edges is deterministic (Section 751) In Section 841, a list scheduling algorithm ill be introduced, employing the technique of reserving time intervals for the leaving edges With list scheduling, utilization of the end or insertion technique is no problem at all.

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