Sum microsystem java

Author: f | 2025-04-24

Download Java software from Sun Microsystems, Java.sun.com, Sun Developer Network (SDN) Downloads. Download java software from sun microsystems. Download Java software from Sun Microsystems Java software manual download page. Get the latest version of the Sun Microsystems Java Runtime Environment (JRE) for Windows, Solaris, and Linux. Download Java software from Sun Microsystems, Java.sun.com, Sun Developer Network (SDN) Downloads. Download java software from sun microsystems. Download Java software from Sun Microsystems Java software manual download page. Get the latest version of the Sun Microsystems Java Runtime Environment (JRE) for Windows, Solaris, and Linux.

Java Install - MicroSystems-NJ.com

8. If we have a function that can be called with theright number of arguments, we don't need to write an anonymous function at all; we can just pass our function by name.In this example, there is some function that adds two integers together, and it's calledInteger::sum. Let's swap it in forour anonymous function: reduce(Integer::sum, 0, list1)reduce(Integer::sum, 0, list1)$62 ==> 6">jshell> reduce(Integer::sum, 0, list1)reduce(Integer::sum, 0, list1)$62 ==> 6Very nice!Wagging our tailOne really cool thing about reduce is that it's a so-called tail-recursive function, meaning that it returns thereturn value of the recursive call directly (or the base case), without needing to fiddle with it. Compare the recursivecall in reduce:return reduce(f, f.apply(acc, first(xs)), rest(xs))to the recursive calls in map and filter:// mapreturn cons(f.apply(first(xs)), map(f, rest(xs)))// filterreturn p.apply(x) ? cons(x, filter(p, rest(xs))) : filter(p, rest(xs))You see how both of them return the result of cons-ing something onto the value returned by the recursive call (in atleast one branch of filter)? That means that the function needs to hold onto the first item of xs in the stack inorder to cons it onto the return value of the recursive call.It turns out this doesn't matter in Java, as Java lacks something calledtail call optimisation (TCO), wherein the compiler translates a tail callinto standard for loop-style iteration. It's pretty neat, but the Java compiler can't do it (yet) because,according to Java architect Brian Goetz,in JDK classes [...] there are a number of security sensitive methods that rely on counting stack frames between JDKlibrary code and calling code to figure out who's calling them.This would break if anything changes the number of frames on the stack (such as eliminating frames on recursive callsthrough tail call optimisation). The good news is that apparently the JDK no longer relies on counting stack frames forthese methods, so TCO will eventually happen, though it's sadly not a priority.And why should we care about TCO? Well, in addition to making code run faster by eliminating a bunch of function calls,TCO lets us call recursive functions on really big lists, which would otherwise cause the JVM to bail with aStackOverflowException when it consumes the maximum allowable number of stack frames, which is limited by the amountof memory the JVM has been given for the stack (which can be controlled by the -Xss command-line argument whenstarting the JVM). Before you ask why not just give the JVM a huge amount of memory for the stack, let's understand thatthe StackOverflowException is actually our friend, as it prevents infinite recursion caused by buggy code fromconsuming all available memory on our machine, causing Linux's out of memory killer (or the equivalent on otheroperating systems) from killing potentially random programs on our machine until things start swapping and then ourmachine slows to a crawl and we can't move our mouse over to the IDE window in order to fix the bug. What a drag!We have taken this brief detour for a reason, which shall now be revealed.Better (but more confusing) map and filterTo prepare ourselves for

Sun Microsystems (JAVA) - Market capitalization

Connection. Class.forName("com.microsoft.sqlserver.jdbc.SQLServerDriver"); con = DriverManager.getConnection(connectionUrl); // Create and execute an SQL statement that returns some data. String SQL = "SELECT Country , SUM(UnitPrice * Quantity) Total " + "FROM value " + "GROUP BY Country " + "WITH (SRC=' stmt = con.createStatement(); rs = stmt.executeQuery(SQL); // Iterate through the data in the result set and display it. while (rs.next()) { System.out.println(rs.getString(1) + " " + rs.getString(2)); } } // Handle any errors that may have occurred. catch (Exception e) { e.printStackTrace(); } finally { if (rs != null) try { rs.close(); } catch (Exception e) {} if (stmt != null) try { stmt.close(); } catch (Exception e) {} if (con != null) try { con.close(); } catch (Exception e) {} } }} Conclusion In this article we discussed how to connect to JDBC-ODBC Bridge in JAVA and integrate data without any coding. Click here to Download JDBC-ODBC Bridge Connector for JAVA and try yourself see how easy it is. If you still have any question(s) then ask here or simply click on live chat icon below and ask our expert (see bottom-right corner of this page).More integrationsOther application integration scenarios for JDBC-ODBC BridgeOther connectors for JAVA Download JDBC-ODBC Bridge Connector for JAVA Documentation Common Searches: How to connect JDBC-ODBC Bridge in JAVA? How to get JDBC-ODBC Bridge data in JAVA? How to read JDBC-ODBC Bridge data in JAVA? How to load JDBC-ODBC Bridge data in JAVA? How to import JDBC-ODBC Bridge data in JAVA? How to pull JDBC-ODBC Bridge data

Java 1.5.0 : Sun Microsystems - Archive.org

Express the concept of consecutive rising in SQL, we have to take an indirect way, that is, calculate the number of consecutive rising days through cumulative number of days that the stock does not rise. This method requires strong skill, making it difficult to code and understand. Moreover, it is difficult to debug SQL, resulting in the maintenance difficulty.Another example, find out the top n customers whose cumulative sales account for half of the total sales, and sort them by sales in descending order:(select sum(amount)/2 from sales)order by amount des">with A as(select client,amount,row_number() over (order by amount) ranknumberfrom sales)select client,amountfrom (select client,amount,sum(amount) over (order by ranknumber) acc from A)where acc>(select sum(amount)/2 from sales)order by amount desIt is difficult to handle the customer who is exactly in the critical position in SQL, so we have to adopt an indirect way, that is, first calculate the cumulative sales in ascending order, and then find out the customers whose cumulative sales is not in the second half of calculation result. This method also requires strong skill, and the code is long and difficult to debug.In addition, SQLite doesn’t provide rich date and string functions. For example: SQLite lacks the function of getting the date before or after a specified number of quarters, and the function of getting the date after N workdays, etc., which limit SQLite and make it unsuitable for scenarios with complex computing requirements.Flow processingSQL itself lacks flow processing capability, so the database will resort to stored procedures to achieve a complete business logic. However, since SQLite does not support stored procedures, it cannot directly achieve a complete business logic, and has to resort to main application. To be specific, first convert SQL’s data objects to the data objects in application (such as Java’s resultSet/List), then use the for/ifstatements of main application to process the flow, and finally convert back to SQL’s data objects. As a result, the code is very cumbersome. When the business logic is very complex, it needs to convert between SQL object and main application object many times, which is more troublesome and related SOL code will not be shown here.Use esProc SPL to solve the difficulties of SQLiteTo provide data processing and computing abilities for small- and micro-Java applications, there is a better choice: esProc SPL.esProc SPL is an open-source data processing engine in Java, and simple in framework and easy to integrate. In addition, esProc SPL is able to store data persistently, and has sufficient computing ability. Such characteristics are similar to those of SQLite.Simple framework: there is no need to configure server, nodes and cluster. As long as the SPL jars are imported, SPL can be deployed in Java environment.SPL provides JDBC driver, making it easy to integrate into Java applications. For simple query tasks, the coding complexity is similar to SQL.1000 && like(Client,"*s*"))");">Class.forName("com.esproc.jdbc.InternalDriver");Connection conn =DriverManager.getConnection("jdbc:esproc:local://");Statement statement = conn.createStatement();ResultSet result = statement.executeQuery("=T("D:/Orders.csv").select(Amount>1000 && like(Client,"*s*"))");SPL supports data persistence and can save data to its own data format (bin file). For example, add records in batches:. Download Java software from Sun Microsystems, Java.sun.com, Sun Developer Network (SDN) Downloads. Download java software from sun microsystems. Download Java software from Sun Microsystems Java software manual download page. Get the latest version of the Sun Microsystems Java Runtime Environment (JRE) for Windows, Solaris, and Linux.

Java Cafe: CERTIFICACIONES EN JAVA DE SUN MICROSYSTEMS

Area as well as by product, which means that there will be multiple data fetching actions (result set function) at the same time, then the delayed cursor mechanism will not work. In this case, do we have to create another cursor to traverse again?No, SPL provides the multipurpose traversal mechanism, enabling us to accomplish multiple types of calculations in one traversal by creating a synchronous channel on the cursor. For example:AB1=file(“orders.txt”).cursor@t(product,area,amount)2cursor A1=A2.groups(area;max(amount))3cursor=A3.groups(product;sum(amount))4cursor=A4.select(amount>=50).total(count(1))Having created the cursor, use the cursor statement to create a channel on it, and attach operations on the channel. We can create multiple channels, if the cursor parameter is not written in the subsequent statements, it indicates the same cursor will be used.With the help of the mechanisms such as cursor, delayed cursor, and multipurpose traversal (channel), SPL can easily handle big data computing. Currently, SPL provides a variety of external storage computing functions and can meet almost all big data computing requirements, which makes SPL far superior to Java and Python.Parallel computingFor big data computing, the performance is critical. We know that parallel computing can effectively improve computing efficiency. Besides the delayed cursor and multipurpose traversal that can guarantee the performance to a certain extent, SPL provides a multi-thread parallel processing mechanism to speed up calculation. Likewise, this mechanism is easy to use.AB1=file(“orders.txt”)2fork to(4)=A1.cursor@t(area,amount;A2:4)3return B2.groups(area;sum(amount):amount)4=A2.conj().groups(area;sum(amount))The fork statement will start multiple threads to execute their own code blocks in parallel, and the number of threads is determined by the parameter following the fork. Moreover, the fork statement will assign these parameters to each thread in turn. When all threads are executed, the calculation result of each thread will be collected and concatenated for further operation.Compared with Java and Python, SPL is much more convenient while using fork to start multiple threads for parallel computing. However, such SPL code is still a bit cumbersome, especially for counting the data of common single table and, attention should also be given that it may need to change the function (from count to sum) when re-aggregating the results returned from threads. To solve this problem, SPL provides a simpler syntax: multi-cursor, which can directly generate parallel cursors.A1=file(“orders.txt”)2=A1.cursor@tm(area,amount;4)3=A2.groups(area;sum(amount):amount)Using the @m option can create parallel multi-cursor, and the subsequent usage is the same as that of single cursor, and SPL will automatically execute parallel computing and re-aggregate the results.Multipurpose traversal can also be implemented on multi-cursor.AB1=file("orders.txt").cursor@tm(area,amount;4)2cursor A1=A2.groups(area;sum(amount):amount)3cursor=A3.groups(product;sum(amount):amount)By means of simple and easy-to-use parallel computing,

Sun Microsystem Java Studio/Java Workshop 2.0 IDE for

AA side chain length)listXL a list of experimentally determined cross-linked lysine residues.Remove all non-protein atoms in xyz.pdb and assign protein atoms a van der Waals radius sum of SURFNET atom radii + solvent radiusSelect a random lysine pair (Ki,Kj) from listXL,Check Euclidean distance (Euc) of (Ki,Kj). Continue, if Euc > maxdist, disregard otherwise and go back to 3.Generate a grid of size maxdist and grid spacing 1 Angstroem centered at AAaSet Integer.MAX_VALUE as distance for all grid cells and label grid cells as residing in theproteinsolventboundary between protein and solvent.Label grid cells residing in (Ki,Kj) as solventSet distance dist = 0.0 for central grid cell of Ki and store grid cell in the active list listactiveStart breadth-first search. Iterate through listactiveCheck that grid cell i is labeled as solventFind all immediate neighbors listneighbourIterate through listneighbour1. Check that grid cell j is labeled as solvent2. Compute new distance for grid cell j as the sum of the distance in grid cell i and the Euclidean distance between grid cell i and j3. If distance sum in 9.3.2 is smaller than the current distance in grid cell j, store the distance sum as new distance for grid cell j and add grid cell j to the new active list listnew_active,Go back to step 9. with listactive = listnew_active.#NOTESAs the SAS distance is based on a grid calculation, the default heap size ofthe Java VM with 64MB is likely to be too small. You can increase the heapsize with java -Xmx512mYou can obtain PyMOL here for free.Beware that in order for PyMOL to recognize the script file, the file musthave the name ending .pml.You can load the script directly at the startup of PyMOL, i.e. with thecommand#CONTACTabdullah.kahraman@uzh.ch#LICENCEXwalk executable and libraries are available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License via the Xwalk website.Anyone is free:to copy, modify, distribute the software;Under the following conditions:the original authors must be given credit by citing the original Xwalk paper:Kahraman A., Malmström L., Aebersold R. (2011). Xwalk: Computing andVisualizing Distances in Cross-linking Experiments. Bioinformatics,doi:10.1093/bioinformatics/btr348.the software or derivate works must not be used for commercial purposesderivate works must

Les certifications Java chez Sun Microsystems

We've accumulated (pun not originally intended but now revelled in), filterR shouldbe straightforward: PVector filterR(Function pred, PVector xs) { return reverse( reduce( (PVector acc, T x) -> pred.apply(x) ? cons(x, acc) : acc, TreePVector.empty(), xs ) );}">public static T> PVectorT> filterR(FunctionT, Boolean> pred, PVectorT> xs) { return reverse( reduce( (PVectorT> acc, T x) -> pred.apply(x) ? cons(x, acc) : acc, TreePVector.empty(), xs ) );}And now, for the moment of truth: filterR(x -> x % 2 > 0, list1)filterR(x -> x % 2 > 0, list1)$70 ==> [1, 3]">jshell> filterR(x -> x % 2 > 0, list1)filterR(x -> x % 2 > 0, list1)$70 ==> [1, 3]Tying it all togetherNow that we understand how map, filter, and reduce work at a very low level, let's solve a problemusing them all in concert:What is the sum of the squares of all the odd numbers between 1 and 10?If we break this down into its constituent parts, we need to:Take the odd numbers between 1 and 10 (filter)Square each of them (map)Sum them all (reduce)Saying that in code looks like this: x * x, filter( x -> x % 2 > 0, TreePVector.from(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) ) ))">reduce( Integer::sum, 0, map( x -> x * x, filter( x -> x % 2 > 0, TreePVector.from(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) ) ))Which JShell tells us evaluates to 165. We'll just take it at its word, to be honest.We are now functional programmers, and can congratulate ourselves heartily!But... looking at our code, we come to the following two conclusions:This doesn't look like any Java we've seenThis is pretty uglyThe good news is that we can do better, and Java will help us! Let's get into that in the next section.Getting idiomatic with itLet's now move from simple integers into a slightly more realistic domain: money!Our new problem is fairly straightforward. We need to take a list of prices, and then:Select the ones for which VAT (Value Added Tax) appliesApply VAT to the priceSum up the total amountAssuming we have the right functions written, that could look something like this: VAT.hasVAT(price.currency()), prices)))">reduce(Price::sum, 0, map(VAT::applyVAT, filter(price -> VAT.hasVAT(price.currency()), prices)))The main problem with this is that it reads backwards. When we described the problem, we effectively said filter,map, then reduce, but when we wrote the code, we said reduce, map, filter.Java 17 gives us some nice tools to turn this around, so let's take a look!Naively applying VATLet's start by defining a Price class to represent a price, which consists of two things: an amount in minor units(for example, cents, öre, etc.), and an ISO-4217 currency code. We can say this in Java like so:public class Price { private long amount; private String currency; public Price(long amount, String currency) { this.amount = amount; this.currency = currency; } public long getAmount() { return amount; } public String getCurrency() { return currency; }}We'll keep up our practice of using JShell to make sure that everything is going well, so. Download Java software from Sun Microsystems, Java.sun.com, Sun Developer Network (SDN) Downloads. Download java software from sun microsystems. Download Java software from Sun Microsystems Java software manual download page. Get the latest version of the Sun Microsystems Java Runtime Environment (JRE) for Windows, Solaris, and Linux. Download Java software from Sun Microsystems, Java.sun.com, Sun Developer Network (SDN) Downloads. Download java software from sun microsystems. Download Java software from Sun Microsystems Java software manual download page. Get the latest version of the Sun Microsystems Java Runtime Environment (JRE) for Windows, Solaris, and Linux.