LEADER 00835nam a2200229 i 4500 001 991000197959707536 005 20020509163515.0 008 010704s1983 ||| ||| | ||| 035 $ab11324491-39ule_inst 035 $aPARLA203824$9ExL 040 $aDip.to Filosofia$bita 100 1 $aAllard, Georges$090863 245 13$aLe scienze fisiche /$cdi G. Allard ... [et al.] ; prefazione di René Taton 260 $c1983 300 $aXXIX, 446 p., [46] c. di tav. :$bill. 490 0 $aStoria della scienza contemporanea ;$v1 907 $a.b11324491$b01-03-17$c01-07-02 912 $a991000197959707536 945 $aLE005IF LI D 33 I$g1$iLE005IFA-SN207$lle005$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i11496034$z01-07-02 996 $aScienze fisiche$9824134 997 $aUNISALENTO 998 $ale005$b01-01-01$cm$da $e-$feng$gxx $h3$i1 LEADER 00838nam0-2200265 --450 001 9910806397103321 005 20240229115158.0 100 $a20240229d1905----kmuy0itay5050 ba 101 0 $aeng 102 $aUS 105 $aa 001yy 200 1 $aBibliographical index of North American fungi$fby William G. Farlow 210 $aWashington$cThe Carnegie Institution of Washington$d1905- 215 $avolumi$d25 cm 327 $a1.1: Abrothallus to badhamia 610 0 $aFunghi$aAmerica settentrionale 676 $a579.5$v23$zita 700 1$aFarlow,$bWilliam Gilson$f<1844-1919>$01677972 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aBK 912 $a9910806397103321 952 $aA PAT 2128-1.1$b1823/2024$fFAGBC 959 $aFAGBC 996 $aBibliographical index of North American fungi$94045268 997 $aUNINA LEADER 06220nam 22006735 450 001 9910300643303321 005 20250609110113.0 010 $a1-4842-1103-0 024 7 $a10.1007/978-1-4842-1103-8 035 $a(CKB)3710000000379532 035 $a(EBL)2094431 035 $a(SSID)ssj0001465500 035 $a(PQKBManifestationID)11825655 035 $a(PQKBTitleCode)TC0001465500 035 $a(PQKBWorkID)11471552 035 $a(PQKB)10729802 035 $a(DE-He213)978-1-4842-1103-8 035 $a(MiAaPQ)EBC2094431 035 $a(CaSebORM)9781484211038 035 $a(PPN)18488960X 035 $a(MiAaPQ)EBC3109112 035 $a(EXLCZ)993710000000379532 100 $a20150328d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aExpert T-SQL Window Functions in SQL Server /$fby Kathi Kellenberger, Clayton Groom 205 $a1st ed. 2015. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2015. 215 $a1 online resource (140 p.) 225 1 $aExpert's Voice in SQL Server 300 $aIncludes index. 311 08$a1-4842-1104-9 327 $aContents at a Glance; Chapter 1: Looking Through the Window; Discovering Window Functions; Thinking About the Window; Understanding the OVER Clause; Dividing Windows with Partitions; Uncovering Special Case Windows; Summary; Chapter 2: Discovering Ranking Functions; Using ROW_NUMBER; Understanding RANK and DENSE_RANK; Dividing Data with NTILE; Solving Queries with Ranking Functions; Deduplicating Data; Finding the First N Rows of Every Group; Solving the Islands Problem; Solving the Bonus Problem; Summary; Chapter 3: Summarizing with Window Aggregates; Using Window Aggregates 327 $aAdding Window Aggregates to Aggregate QueriesUsing Window Aggregates to Solve Common Queries; The Percent of Sales Problem; The Partitioned Table Problem; Creating Custom Window Aggregate Functions; Summary; Chapter 4: Tuning for Better Performance; Using Execution Plans; Using STATISTICS IO; Understanding the Performance Implications of Window Aggregates; Indexing to Improve the Performance of Window Functions; Performing Time Comparisons; Summary; Chapter 5: Calculating Running and Moving Aggregates; Adding ORDER BY to Window Aggregates; Calculating Moving Totals and Averages 327 $aSolving Queries Using Accumulating AggregatesThe Last Good Value Problem; The Subscription Problem; Summary; Chapter 6: Adding Frames to the Window; Understanding Framing; Applying Frames to Running and Moving Aggregates; Measuring Performance; Understanding the Logical Difference Between ROWS and RANGE; Summary; Chapter 7: Taking a Peek at Another Row; Understanding LAG and LEAD; Understanding FIRST_VALUE and LAST_ VALUE; Using the Offset Functions to Solve Queries; The Year-Over-Year Growth Calculation; The Gaps Problem; Comparing Performance; LAG and LEAD Performance 327 $aFIRST_VALUE and LAST_VALUE PERFORMANCESummary; Chapter 8: Understanding Statistical Functions; Using PERCENT_RANK and CUME_ DIST; Using PERCENTILE_CONT and PERCENTILE_ DISC; Comparing Statistical Functions to Older Methods; Summary; Chapter 9: Time Range Calculations and Trends; Putting It All Together; Percent of Parent; Period-to-Date Calculations; Averages, Moving Averages, and Rate-of-Change; Same Period Prior Year; Difference and Percent Difference; Moving Totals and Simple Moving Averages; Rate-of-Change Calculations; Summary; Index; Contents; About the Authors 327 $aAbout the Technical ReviewerAcknowledgments; Author's Note 330 $aExpert T-SQL Window Functions in SQL Server takes you from any level of knowledge of windowing functions and turns you into an expert who can use these powerful functions to solve many T-SQL queries. Replace slow cursors and self-joins with queries that are easy to write and fantastically better performing, all through the magic of window functions. First introduced in SQL Server 2005, window functions came into full blossom with SQL Server 2012. They truly are one of the most notable developments in SQL in a decade, and every developer and DBA can benefit from their expressive power in solving day-to-day business problems. Begin using windowing functions like ROW_NUMBER and LAG, and you will discover more ways to use them every day. You will approach SQL Server queries in a different way, thinking about sets of data instead of individual rows. Your queries will run faster, they will be easier to write, and they will be easier to deconstruct and maintain and enhance in the future. Just knowing and using these functions is not enough. You also need to understand how to tune the queries. Expert T-SQL Window Functions in SQL Server explains clearly how to get the best performance. The book also covers the rare cases when older techniques are the best bet. Stop using cursors and self-joins to solve complicated queries. Become a T-SQL expert by mastering windowing functions. Teaches you how to use all the window functions introduced in 2005 and 2012. Provides real-world examples that you can experiment with in your own database. Explains how to get the best performance when using windowing functions. 410 0$aExpert's voice in SQL server. 606 $aDatabase management 606 $aProgramming languages (Electronic computers) 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 606 $aProgramming Languages, Compilers, Interpreters$3https://scigraph.springernature.com/ontologies/product-market-codes/I14037 615 0$aDatabase management. 615 0$aProgramming languages (Electronic computers) 615 14$aDatabase Management. 615 24$aProgramming Languages, Compilers, Interpreters. 676 $a004 676 $a005.13 676 $a005.74 700 $aKellenberger$b Kathi$4aut$4http://id.loc.gov/vocabulary/relators/aut$0879538 702 $aGroom$b Clayton$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910300643303321 996 $aExpert T-SQL Window Functions in SQL Server$91963815 997 $aUNINA