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  • How can I update a column in a table with the result of a select statement that uses row being updat

    - by Sailing Judo
    This SQL statement example is very close to what I think I need... update table1 set value1 = x.value1 from (select value1, code from table2 where code = something) as x However, what I need to do is change the "something" in the above example to a value from the row that is being updated. For example, I tried this but it didn't work: update table1 A set value1 = x.value1 from (select value1, code from table2 where code = A.something) as x This is a one time operation to update an existing table and I'm not really looking for high performance way to do this. Any solution that gets the task done is good enough.

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  • Why does `Array(0,1,2) == Array(0,1,2)` not return the expected result?

    - by soc
    As far as I understand, Scala's == defines the natural equality of two objects. I expected that Array(0,1,2) == Array(0,1,2) compares the natural equality e. g. checks if all elements of the array return true when compared with the corresponding elements of the other array. People told me that Scala's Array is just a Java [] which only compares identity. But Scala's String is also just a Java String but Scala overrides equals to compare natural equality. I wonder why Array's equals method was not overridden, too. Thank you for your thoughts!

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  • contents().find() not producing the same result as changing selector context? - jQuery

    - by Alex
    Hello all, I have a function that looks somewhat like this: function(domObj) { var currentObj = $(domObj); ... currentObj.contents().find(".ws").after("foobar"); } My problem is that the above method of using .contents().find() is not working. "foobar" never gets stuffed after the specified dom element, represented by the selector, .ws However if I do this: $(".ws", currentObj).after("foobar"); Then the string, "foobar" gets appended every time. My question: Are not these two methods supposed to be equivilant? How/what am I doing wrong in my use of .contents().find() so that it is not working? Thanks!

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  • In a JDBC ResultSet, what should happen when getLong() or getShort() is called on an int result colu

    - by Uri
    Say that I have a JDBC ResultSet, and I call the getLong() or getshort() method. For which of the following SQL types {SMALLINT, INT, BIGINT} should I get long, and for which types should I get an error? In other words, if I have an INT and I want a SMALLINT (A short), would I get it, or would I get an error? Similarly, if I have an INT and want a BIGINT (a long), would I get it, or would I get an error? The Javadocs (listed below) say nothing. public long getLong(int columnIndex) throws SQLException Retrieves the value of the designated column in the current row of this ResultSet object as a long in the Java programming language. Parameters: columnIndex - the first column is 1, the second is 2, ... Returns: the column value; if the value is SQL NULL, the value returned is 0 Throws: SQLException - if a database access error occurs

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  • Sun Fire X4800 M2 Delivers World Record TPC-C for x86 Systems

    - by Brian
    Oracle's Sun Fire X4800 M2 server equipped with eight 2.4 GHz Intel Xeon Processor E7-8870 chips obtained a result of 5,055,888 tpmC on the TPC-C benchmark. This result is a world record for x86 servers. Oracle demonstrated this world record database performance running Oracle Database 11g Release 2 Enterprise Edition with Partitioning. The Sun Fire X4800 M2 server delivered a new x86 TPC-C world record of 5,055,888 tpmC with a price performance of $0.89/tpmC using Oracle Database 11g Release 2. This configuration is available 06/26/12. The Sun Fire X4800 M2 server delivers 3.0x times better performance than the next 8-processor result, an IBM System p 570 equipped with POWER6 processors. The Sun Fire X4800 M2 server has 3.1x times better price/performance than the 8-processor 4.7GHz POWER6 IBM System p 570. The Sun Fire X4800 M2 server has 1.6x times better performance than the 4-processor IBM x3850 X5 system equipped with Intel Xeon processors. This is the first TPC-C result on any system using eight Intel Xeon Processor E7-8800 Series chips. The Sun Fire X4800 M2 server is the first x86 system to get over 5 million tpmC. The Oracle solution utilized Oracle Linux operating system and Oracle Database 11g Enterprise Edition Release 2 with Partitioning to produce the x86 world record TPC-C benchmark performance. Performance Landscape Select TPC-C results (sorted by tpmC, bigger is better) System p/c/t tpmC Price/tpmC Avail Database MemorySize Sun Fire X4800 M2 8/80/160 5,055,888 0.89 USD 6/26/2012 Oracle 11g R2 4 TB IBM x3850 X5 4/40/80 3,014,684 0.59 USD 7/11/2011 DB2 ESE 9.7 3 TB IBM x3850 X5 4/32/64 2,308,099 0.60 USD 5/20/2011 DB2 ESE 9.7 1.5 TB IBM System p 570 8/16/32 1,616,162 3.54 USD 11/21/2007 DB2 9.0 2 TB p/c/t - processors, cores, threads Avail - availability date Oracle and IBM TPC-C Response times System tpmC Response Time (sec) New Order 90th% Response Time (sec) New Order Average Sun Fire X4800 M2 5,055,888 0.210 0.166 IBM x3850 X5 3,014,684 0.500 0.272 Ratios - Oracle Better 1.6x 1.4x 1.3x Oracle uses average new order response time for comparison between Oracle and IBM. Graphs of Oracle's and IBM's response times for New-Order can be found in the full disclosure reports on TPC's website TPC-C Official Result Page. Configuration Summary and Results Hardware Configuration: Server Sun Fire X4800 M2 server 8 x 2.4 GHz Intel Xeon Processor E7-8870 4 TB memory 8 x 300 GB 10K RPM SAS internal disks 8 x Dual port 8 Gbs FC HBA Data Storage 10 x Sun Fire X4270 M2 servers configured as COMSTAR heads, each with 1 x 3.06 GHz Intel Xeon X5675 processor 8 GB memory 10 x 2 TB 7.2K RPM 3.5" SAS disks 2 x Sun Storage F5100 Flash Array storage (1.92 TB each) 1 x Brocade 5300 switches Redo Storage 2 x Sun Fire X4270 M2 servers configured as COMSTAR heads, each with 1 x 3.06 GHz Intel Xeon X5675 processor 8 GB memory 11 x 2 TB 7.2K RPM 3.5" SAS disks Clients 8 x Sun Fire X4170 M2 servers, each with 2 x 3.06 GHz Intel Xeon X5675 processors 48 GB memory 2 x 300 GB 10K RPM SAS disks Software Configuration: Oracle Linux (Sun Fire 4800 M2) Oracle Solaris 11 Express (COMSTAR for Sun Fire X4270 M2) Oracle Solaris 10 9/10 (Sun Fire X4170 M2) Oracle Database 11g Release 2 Enterprise Edition with Partitioning Oracle iPlanet Web Server 7.0 U5 Tuxedo CFS-R Tier 1 Results: System: Sun Fire X4800 M2 tpmC: 5,055,888 Price/tpmC: 0.89 USD Available: 6/26/2012 Database: Oracle Database 11g Cluster: no New Order Average Response: 0.166 seconds Benchmark Description TPC-C is an OLTP system benchmark. It simulates a complete environment where a population of terminal operators executes transactions against a database. The benchmark is centered around the principal activities (transactions) of an order-entry environment. These transactions include entering and delivering orders, recording payments, checking the status of orders, and monitoring the level of stock at the warehouses. Key Points and Best Practices Oracle Database 11g Release 2 Enterprise Edition with Partitioning scales easily to this high level of performance. COMSTAR (Common Multiprotocol SCSI Target) is the software framework that enables an Oracle Solaris host to serve as a SCSI Target platform. COMSTAR uses a modular approach to break the huge task of handling all the different pieces in a SCSI target subsystem into independent functional modules which are glued together by the SCSI Target Mode Framework (STMF). The modules implementing functionality at SCSI level (disk, tape, medium changer etc.) are not required to know about the underlying transport. And the modules implementing the transport protocol (FC, iSCSI, etc.) are not aware of the SCSI-level functionality of the packets they are transporting. The framework hides the details of allocation providing execution context and cleanup of SCSI commands and associated resources and simplifies the task of writing the SCSI or transport modules. Oracle iPlanet Web Server middleware is used for the client tier of the benchmark. Each web server instance supports more than a quarter-million users while satisfying the response time requirement from the TPC-C benchmark. See Also Oracle Press Release -- Sun Fire X4800 M2 TPC-C Executive Summary tpc.org Complete Sun Fire X4800 M2 TPC-C Full Disclosure Report tpc.org Transaction Processing Performance Council (TPC) Home Page Ideas International Benchmark Page Sun Fire X4800 M2 Server oracle.com OTN Oracle Linux oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Sun Storage F5100 Flash Array oracle.com OTN Disclosure Statement TPC Benchmark C, tpmC, and TPC-C are trademarks of the Transaction Processing Performance Council (TPC). Sun Fire X4800 M2 (8/80/160) with Oracle Database 11g Release 2 Enterprise Edition with Partitioning, 5,055,888 tpmC, $0.89 USD/tpmC, available 6/26/2012. IBM x3850 X5 (4/40/80) with DB2 ESE 9.7, 3,014,684 tpmC, $0.59 USD/tpmC, available 7/11/2011. IBM x3850 X5 (4/32/64) with DB2 ESE 9.7, 2,308,099 tpmC, $0.60 USD/tpmC, available 5/20/2011. IBM System p 570 (8/16/32) with DB2 9.0, 1,616,162 tpmC, $3.54 USD/tpmC, available 11/21/2007. Source: http://www.tpc.org/tpcc, results as of 7/15/2011.

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  • Partition Wise Joins

    - by jean-pierre.dijcks
    Some say they are the holy grail of parallel computing and PWJ is the basis for a shared nothing system and the only join method that is available on a shared nothing system (yes this is oversimplified!). The magic in Oracle is of course that is one of many ways to join data. And yes, this is the old flexibility vs. simplicity discussion all over, so I won't go there... the point is that what you must do in a shared nothing system, you can do in Oracle with the same speed and methods. The Theory A partition wise join is a join between (for simplicity) two tables that are partitioned on the same column with the same partitioning scheme. In shared nothing this is effectively hard partitioning locating data on a specific node / storage combo. In Oracle is is logical partitioning. If you now join the two tables on that partitioned column you can break up the join in smaller joins exactly along the partitions in the data. Since they are partitioned (grouped) into the same buckets, all values required to do the join live in the equivalent bucket on either sides. No need to talk to anyone else, no need to redistribute data to anyone else... in short, the optimal join method for parallel processing of two large data sets. PWJ's in Oracle Since we do not hard partition the data across nodes in Oracle we use the Partitioning option to the database to create the buckets, then set the Degree of Parallelism (or run Auto DOP - see here) and get our PWJs. The main questions always asked are: How many partitions should I create? What should my DOP be? In a shared nothing system the answer is of course, as many partitions as there are nodes which will be your DOP. In Oracle we do want you to look at the workload and concurrency, and once you know that to understand the following rules of thumb. Within Oracle we have more ways of joining of data, so it is important to understand some of the PWJ ideas and what it means if you have an uneven distribution across processes. Assume we have a simple scenario where we partition the data on a hash key resulting in 4 hash partitions (H1 -H4). We have 2 parallel processes that have been tasked with reading these partitions (P1 - P2). The work is evenly divided assuming the partitions are the same size and we can scan this in time t1 as shown below. Now assume that we have changed the system and have a 5th partition but still have our 2 workers P1 and P2. The time it takes is actually 50% more assuming the 5th partition has the same size as the original H1 - H4 partitions. In other words to scan these 5 partitions, the time t2 it takes is not 1/5th more expensive, it is a lot more expensive and some other join plans may now start to look exciting to the optimizer. Just to post the disclaimer, it is not as simple as I state it here, but you get the idea on how much more expensive this plan may now look... Based on this little example there are a few rules of thumb to follow to get the partition wise joins. First, choose a DOP that is a factor of two (2). So always choose something like 2, 4, 8, 16, 32 and so on... Second, choose a number of partitions that is larger or equal to 2* DOP. Third, make sure the number of partitions is divisible through 2 without orphans. This is also known as an even number... Fourth, choose a stable partition count strategy, which is typically hash, which can be a sub partitioning strategy rather than the main strategy (range - hash is a popular one). Fifth, make sure you do this on the join key between the two large tables you want to join (and this should be the obvious one...). Translating this into an example: DOP = 8 (determined based on concurrency or by using Auto DOP with a cap due to concurrency) says that the number of partitions >= 16. Number of hash (sub) partitions = 32, which gives each process four partitions to work on. This number is somewhat arbitrary and depends on your data and system. In this case my main reasoning is that if you get more room on the box you can easily move the DOP for the query to 16 without repartitioning... and of course it makes for no leftovers on the table... And yes, we recommend up-to-date statistics. And before you start complaining, do read this post on a cool way to do stats in 11.

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  • Can a recursive function have iterations/loops?

    - by Omega
    I've been studying about recursive functions, and apparently, they're functions that call themselves, and don't use iterations/loops (otherwise it wouldn't be a recursive function). However, while surfing the web for examples (the 8-queens-recursive problem), I found this function: private boolean placeQueen(int rows, int queens, int n) { boolean result = false; if (row < n) { while ((queens[row] < n - 1) && !result) { queens[row]++; if (verify(row,queens,n)) { ok = placeQueen(row + 1,queens,n); } } if (!result) { queens[row] = -1; } }else{ result = true; } return result; } There is a while loop involved. ... so I'm a bit lost now. Can I use loops or not?

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  • Windows in StreamInsight: Hopping vs. Snapshot

    - by Roman Schindlauer
    Three weeks ago, we explained the basic concept of windows in StreamInsight: defining sets of events that serve as arguments for set-based operations, like aggregations. Today, we want to discuss the so-called Hopping Windows and compare them with Snapshot Windows. We will compare these two, because they can serve similar purposes with different behaviors; we will discuss the remaining window type, Count Windows, another time. Hopping (and its syntactic-sugar-sister Tumbling) windows are probably the most straightforward windowing concept in StreamInsight. A hopping window is defined by its length, and the offset from one window to the next. They are aligned with some absolute point on the timeline (which can also be given as a parameter to the window) and create sets of events. The diagram below shows an example of a hopping window with length of 1h and hop size (the offset) of 15 minutes, hence creating overlapping windows:   Two aspects in this diagram are important: Since this window is overlapping, an event can fall into more than one windows. If an (interval) event spans a window boundary, its lifetime will be clipped to the window, before it is passed to the set-based operation. That’s the default and currently only available window input policy. (This should only concern you if you are using a time-sensitive user-defined aggregate or operator.) The set-based operation will be applied to each of these sets, yielding a result. This result is: A single scalar value in case of built-in or user-defined aggregates. A subset of the input payloads, in case of the TopK operator. Arbitrary events, when using a user-defined operator. The timestamps of the result are almost always the ones of the windows. Only the user-defined  operator can create new events with timestamps. (However, even these event lifetimes are subject to the window’s output policy, which is currently always to clip to the window end.) Let’s assume we were calculating the sum over some payload field: var result = from window in source.HoppingWindow( TimeSpan.FromHours(1), TimeSpan.FromMinutes(15), HoppingWindowOutputPolicy.ClipToWindowEnd) select new { avg = window.Avg(e => e.Value) }; Now each window is reflected by one result event:   As you can see, the window definition defines the output frequency. No matter how many or few events we got from the input, this hopping window will produce one result every 15 minutes – except for those windows that do not contain any events at all, because StreamInsight window operations are empty-preserving (more about that another time). The “forced” output for every window can become a performance issue if you have a real-time query with many events in a wide group & apply – let me explain: imagine you have a lot of events that you group by and then aggregate within each group – classical streaming pattern. The hopping window produces a result in each group at exactly the same point in time for all groups, since the window boundaries are aligned with the timeline, not with the event timestamps. This means that the query output will become very bursty, delivering the results of all the groups at the same point in time. This becomes especially obvious if the events are long-lasting, spanning multiple windows each, so that the produced result events do not change their value very often. In such a case, a snapshot window can remedy. Snapshot windows are more difficult to explain than hopping windows: they represent those periods in time, when no event changes occur. In other words, if you mark all event start and and times on your timeline, then you are looking at all snapshot window boundaries:   If your events are never overlapping, the snapshot window will not make much sense. It is commonly used together with timestamp modification, which make it a very powerful tool. Or as Allan Mitchell expressed in in a recent tweet: “I used to look at SnapshotWindow() with disdain. Now she is my mistress, the one I turn to in times of trouble and need”. Let’s look at a simple example: I want to compute the average of some value in my events over the last minute. I don’t want this output be produced at fixed intervals, but at soon as it changes (that’s the true event-driven spirit!). The snapshot window will include all currently active event at each point in time, hence we need to extend our original events’ lifetimes into the future: Applying the Snapshot window on these events, it will appear to be “looking back into the past”: If you look at the result produced in this diagram, you can easily prove that, at each point in time, the current event value represents the average of all original input event within the last minute. Here is the LINQ representation of that query, applying the lifetime extension before the snapshot window: var result = from window in source .AlterEventDuration(e => TimeSpan.FromMinutes(1)) .SnapshotWindow(SnapshotWindowOutputPolicy.Clip) select new { avg = window.Avg(e => e.Value) }; With more complex modifications of the event lifetimes you can achieve many more query patterns. For instance “running totals” by keeping the event start times, but snapping their end times to some fixed time, like the end of the day. Each snapshot then “sees” all events that have happened in the respective time period so far. Regards, The StreamInsight Team

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  • Does a lead-to screen with AdSense ad conform to Google's rules?

    - by ElHaix
    Re: Google's ad placement policy I have noticed that when clicking on some Forbes links, I am taken to a screen with an ad in the middle - at the top there is a link to skip the ad. Upon clicking on the skip link I am taken to the article I want to view. I want to implement something similar on my sites, where, when clicking on a search result, a the results window first displays one AdSense add on the screen with a similar UI as what I saw on Forbes. Currently, when a user clicks on a result, a new tab/window opens with the result. What I am proposing is that before the result appears, the screen displays a "Continue to result" link at the top in large letters, and in the center of the page, "Advertisement" with the ad below. This is the only popup that is user initiated and there are no other popups on the site. Navigation elements are not modified in any way. Will I get penalized by Google for implementing this?

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  • Memory not being freed, causing giant memory leak

    - by Delan Azabani
    In my Unicode library for C++, the ustring class has operator= functions set for char* values and other ustring values. When doing the simple memory leak test: #include <cstdio> #include "ucpp" main() { ustring a; for(;;)a="MEMORY"; } the memory used by the program grows uncontrollably (characteristic of a program with a big memory leak) even though I've added free() calls to both of the functions. I am unsure why this is ineffective (am I missing free() calls in other places?) This is the current library code: #include <cstdlib> #include <cstring> class ustring { int * values; long len; public: long length() { return len; } ustring() { len = 0; values = (int *) malloc(0); } ustring(const ustring &input) { len = input.len; values = (int *) malloc(sizeof(int) * len); for (long i = 0; i < len; i++) values[i] = input.values[i]; } ustring operator=(ustring input) { ustring result(input); free(values); len = input.len; values = input.values; return * this; } ustring(const char * input) { values = (int *) malloc(0); long s = 0; // s = number of parsed chars int a, b, c, d, contNeed = 0, cont = 0; for (long i = 0; input[i]; i++) if (input[i] < 0x80) { // ASCII, direct copy (00-7f) values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = input[i]; } else if (input[i] < 0xc0) { // this is a continuation (80-bf) if (cont == contNeed) { // no need for continuation, use U+fffd values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = 0xfffd; } cont = cont + 1; values[s - 1] = values[s - 1] | ((input[i] & 0x3f) << ((contNeed - cont) * 6)); if (cont == contNeed) cont = contNeed = 0; } else if (input[i] < 0xc2) { // invalid byte, use U+fffd (c0-c1) values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = 0xfffd; } else if (input[i] < 0xe0) { // start of 2-byte sequence (c2-df) contNeed = 1; values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = (input[i] & 0x1f) << 6; } else if (input[i] < 0xf0) { // start of 3-byte sequence (e0-ef) contNeed = 2; values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = (input[i] & 0x0f) << 12; } else if (input[i] < 0xf5) { // start of 4-byte sequence (f0-f4) contNeed = 3; values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = (input[i] & 0x07) << 18; } else { // restricted or invalid (f5-ff) values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = 0xfffd; } len = s; } ustring operator=(const char * input) { ustring result(input); free(values); len = result.len; values = result.values; return * this; } ustring operator+(ustring input) { ustring result; result.len = len + input.len; result.values = (int *) malloc(sizeof(int) * result.len); for (long i = 0; i < len; i++) result.values[i] = values[i]; for (long i = 0; i < input.len; i++) result.values[i + len] = input.values[i]; return result; } ustring operator[](long index) { ustring result; result.len = 1; result.values = (int *) malloc(sizeof(int)); result.values[0] = values[index]; return result; } operator char * () { return this -> encode(); } char * encode() { char * r = (char *) malloc(0); long s = 0; for (long i = 0; i < len; i++) { if (values[i] < 0x80) r = (char *) realloc(r, s + 1), r[s + 0] = char(values[i]), s += 1; else if (values[i] < 0x800) r = (char *) realloc(r, s + 2), r[s + 0] = char(values[i] >> 6 | 0x60), r[s + 1] = char(values[i] & 0x3f | 0x80), s += 2; else if (values[i] < 0x10000) r = (char *) realloc(r, s + 3), r[s + 0] = char(values[i] >> 12 | 0xe0), r[s + 1] = char(values[i] >> 6 & 0x3f | 0x80), r[s + 2] = char(values[i] & 0x3f | 0x80), s += 3; else r = (char *) realloc(r, s + 4), r[s + 0] = char(values[i] >> 18 | 0xf0), r[s + 1] = char(values[i] >> 12 & 0x3f | 0x80), r[s + 2] = char(values[i] >> 6 & 0x3f | 0x80), r[s + 3] = char(values[i] & 0x3f | 0x80), s += 4; } return r; } };

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  • Assignment operator that calls a constructor is broken

    - by Delan Azabani
    I've implemented some of the changes suggested in this question, and (thanks very much) it works quite well, however... in the process I've seemed to break the post-declaration assignment operator. With the following code: #include <cstdio> #include "ucpp" main() { ustring a = "test"; ustring b = "ing"; ustring c = "- -"; ustring d = "cafe\xcc\x81"; printf("%s\n", (a + b + c[1] + d).encode()); } I get a nice "testing cafe´" message. However, if I modify the code slightly so that the const char * conversion is done separately, post-declaration: #include <cstdio> #include "ucpp" main() { ustring a = "test"; ustring b = "ing"; ustring c = "- -"; ustring d; d = "cafe\xcc\x81"; printf("%s\n", (a + b + c[1] + d).encode()); } the ustring named d becomes blank, and all that is output is "testing ". My new code has three constructors, one void (which is probably the one being incorrectly used, and is used in the operator+ function), one that takes a const ustring &, and one that takes a const char *. The following is my new library code: #include <cstdlib> #include <cstring> class ustring { int * values; long len; public: long length() { return len; } ustring() { len = 0; values = (int *) malloc(0); } ustring(const ustring &input) { len = input.len; values = (int *) malloc(sizeof(int) * len); for (long i = 0; i < len; i++) values[i] = input.values[i]; } ustring operator=(ustring input) { ustring result(input); return result; } ustring(const char * input) { values = (int *) malloc(0); long s = 0; // s = number of parsed chars int a, b, c, d, contNeed = 0, cont = 0; for (long i = 0; input[i]; i++) if (input[i] < 0x80) { // ASCII, direct copy (00-7f) values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = input[i]; } else if (input[i] < 0xc0) { // this is a continuation (80-bf) if (cont == contNeed) { // no need for continuation, use U+fffd values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = 0xfffd; } cont = cont + 1; values[s - 1] = values[s - 1] | ((input[i] & 0x3f) << ((contNeed - cont) * 6)); if (cont == contNeed) cont = contNeed = 0; } else if (input[i] < 0xc2) { // invalid byte, use U+fffd (c0-c1) values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = 0xfffd; } else if (input[i] < 0xe0) { // start of 2-byte sequence (c2-df) contNeed = 1; values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = (input[i] & 0x1f) << 6; } else if (input[i] < 0xf0) { // start of 3-byte sequence (e0-ef) contNeed = 2; values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = (input[i] & 0x0f) << 12; } else if (input[i] < 0xf5) { // start of 4-byte sequence (f0-f4) contNeed = 3; values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = (input[i] & 0x07) << 18; } else { // restricted or invalid (f5-ff) values = (int *) realloc(values, sizeof(int) * ++s); values[s - 1] = 0xfffd; } len = s; } ustring operator=(const char * input) { ustring result(input); return result; } ustring operator+(ustring input) { ustring result; result.len = len + input.len; result.values = (int *) malloc(sizeof(int) * result.len); for (long i = 0; i < len; i++) result.values[i] = values[i]; for (long i = 0; i < input.len; i++) result.values[i + len] = input.values[i]; return result; } ustring operator[](long index) { ustring result; result.len = 1; result.values = (int *) malloc(sizeof(int)); result.values[0] = values[index]; return result; } char * encode() { char * r = (char *) malloc(0); long s = 0; for (long i = 0; i < len; i++) { if (values[i] < 0x80) r = (char *) realloc(r, s + 1), r[s + 0] = char(values[i]), s += 1; else if (values[i] < 0x800) r = (char *) realloc(r, s + 2), r[s + 0] = char(values[i] >> 6 | 0x60), r[s + 1] = char(values[i] & 0x3f | 0x80), s += 2; else if (values[i] < 0x10000) r = (char *) realloc(r, s + 3), r[s + 0] = char(values[i] >> 12 | 0xe0), r[s + 1] = char(values[i] >> 6 & 0x3f | 0x80), r[s + 2] = char(values[i] & 0x3f | 0x80), s += 3; else r = (char *) realloc(r, s + 4), r[s + 0] = char(values[i] >> 18 | 0xf0), r[s + 1] = char(values[i] >> 12 & 0x3f | 0x80), r[s + 2] = char(values[i] >> 6 & 0x3f | 0x80), r[s + 3] = char(values[i] & 0x3f | 0x80), s += 4; } return r; } };

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  • How do I test UrlHelper.RouteUrl()?

    - by Jeff Putz
    I'm having a tough go trying to figure out what I need to mock in my tests to show that UrlHelper.RouteUrl() is returning the right URL. It works, but I'd like to have the right test coverage. The meat of the controller method looks like this: var urlHelper = new UrlHelper(ControllerContext.RequestContext); return Json(new BasicJsonMessage { Result = true, Redirect = urlHelper.RouteUrl(new { controller = "TheController", action = "TheAction", id = somerecordnumber }) }); Testing the result object is easy enough, like this: var controller = new MyController(); var result = controller.DoTheNewHotness()); Assert.IsInstanceOf<JsonResult>(result); var data = (BasicJsonMessage)result.Data; Assert.IsTrue(data.Result); result.Redirect is always null because the controller obviously doesn't know anything about the routing. What do I have to do to the controller to let it know? As I said, I know it works when I exercise the production code, but I'd like some testing assurance. Thanks for your help!

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  • Node.js Adventure - When Node Flying in Wind

    - by Shaun
    In the first post of this series I mentioned some popular modules in the community, such as underscore, async, etc.. I also listed a module named “Wind (zh-CN)”, which is created by one of my friend, Jeff Zhao (zh-CN). Now I would like to use a separated post to introduce this module since I feel it brings a new async programming style in not only Node.js but JavaScript world. If you know or heard about the new feature in C# 5.0 called “async and await”, or you learnt F#, you will find the “Wind” brings the similar async programming experience in JavaScript. By using “Wind”, we can write async code that looks like the sync code. The callbacks, async stats and exceptions will be handled by “Wind” automatically and transparently.   What’s the Problem: Dense “Callback” Phobia Let’s firstly back to my second post in this series. As I mentioned in that post, when we wanted to read some records from SQL Server we need to open the database connection, and then execute the query. In Node.js all IO operation are designed as async callback pattern which means when the operation was done, it will invoke a function which was taken from the last parameter. For example the database connection opening code would be like this. 1: sql.open(connectionString, function(error, conn) { 2: if(error) { 3: // some error handling code 4: } 5: else { 6: // connection opened successfully 7: } 8: }); And then if we need to query the database the code would be like this. It nested in the previous function. 1: sql.open(connectionString, function(error, conn) { 2: if(error) { 3: // some error handling code 4: } 5: else { 6: // connection opened successfully 7: conn.queryRaw(command, function(error, results) { 8: if(error) { 9: // failed to execute this command 10: } 11: else { 12: // records retrieved successfully 13: } 14: }; 15: } 16: }); Assuming if we need to copy some data from this database to another then we need to open another connection and execute the command within the function under the query function. 1: sql.open(connectionString, function(error, conn) { 2: if(error) { 3: // some error handling code 4: } 5: else { 6: // connection opened successfully 7: conn.queryRaw(command, function(error, results) { 8: if(error) { 9: // failed to execute this command 10: } 11: else { 12: // records retrieved successfully 13: target.open(targetConnectionString, function(error, t_conn) { 14: if(error) { 15: // connect failed 16: } 17: else { 18: t_conn.queryRaw(copy_command, function(error, results) { 19: if(error) { 20: // copy failed 21: } 22: else { 23: // and then, what do you want to do now... 24: } 25: }; 26: } 27: }; 28: } 29: }; 30: } 31: }); This is just an example. In the real project the logic would be more complicated. This means our application might be messed up and the business process will be fragged by many callback functions. I would like call this “Dense Callback Phobia”. This might be a challenge how to make code straightforward and easy to read, something like below. 1: try 2: { 3: // open source connection 4: var s_conn = sqlConnect(s_connectionString); 5: // retrieve data 6: var results = sqlExecuteCommand(s_conn, s_command); 7: 8: // open target connection 9: var t_conn = sqlConnect(t_connectionString); 10: // prepare the copy command 11: var t_command = getCopyCommand(results); 12: // execute the copy command 13: sqlExecuteCommand(s_conn, t_command); 14: } 15: catch (ex) 16: { 17: // error handling 18: }   What’s the Problem: Sync-styled Async Programming Similar as the previous problem, the callback-styled async programming model makes the upcoming operation as a part of the current operation, and mixed with the error handling code. So it’s very hard to understand what on earth this code will do. And since Node.js utilizes non-blocking IO mode, we cannot invoke those operations one by one, as they will be executed concurrently. For example, in this post when I tried to copy the records from Windows Azure SQL Database (a.k.a. WASD) to Windows Azure Table Storage, if I just insert the data into table storage one by one and then print the “Finished” message, I will see the message shown before the data had been copied. This is because all operations were executed at the same time. In order to make the copy operation and print operation executed synchronously I introduced a module named “async” and the code was changed as below. 1: async.forEach(results.rows, 2: function (row, callback) { 3: var resource = { 4: "PartitionKey": row[1], 5: "RowKey": row[0], 6: "Value": row[2] 7: }; 8: client.insertEntity(tableName, resource, function (error) { 9: if (error) { 10: callback(error); 11: } 12: else { 13: console.log("entity inserted."); 14: callback(null); 15: } 16: }); 17: }, 18: function (error) { 19: if (error) { 20: error["target"] = "insertEntity"; 21: res.send(500, error); 22: } 23: else { 24: console.log("all done."); 25: res.send(200, "Done!"); 26: } 27: }); It ensured that the “Finished” message will be printed when all table entities had been inserted. But it cannot promise that the records will be inserted in sequence. It might be another challenge to make the code looks like in sync-style? 1: try 2: { 3: forEach(row in rows) { 4: var entity = { /* ... */ }; 5: tableClient.insert(tableName, entity); 6: } 7:  8: console.log("Finished"); 9: } 10: catch (ex) { 11: console.log(ex); 12: }   How “Wind” Helps “Wind” is a JavaScript library which provides the control flow with plain JavaScript for asynchronous programming (and more) without additional pre-compiling steps. It’s available in NPM so that we can install it through “npm install wind”. Now let’s create a very simple Node.js application as the example. This application will take some website URLs from the command arguments and tried to retrieve the body length and print them in console. Then at the end print “Finish”. I’m going to use “request” module to make the HTTP call simple so I also need to install by the command “npm install request”. The code would be like this. 1: var request = require("request"); 2:  3: // get the urls from arguments, the first two arguments are `node.exe` and `fetch.js` 4: var args = process.argv.splice(2); 5:  6: // main function 7: var main = function() { 8: for(var i = 0; i < args.length; i++) { 9: // get the url 10: var url = args[i]; 11: // send the http request and try to get the response and body 12: request(url, function(error, response, body) { 13: if(!error && response.statusCode == 200) { 14: // log the url and the body length 15: console.log( 16: "%s: %d.", 17: response.request.uri.href, 18: body.length); 19: } 20: else { 21: // log error 22: console.log(error); 23: } 24: }); 25: } 26: 27: // finished 28: console.log("Finished"); 29: }; 30:  31: // execute the main function 32: main(); Let’s execute this application. (I made them in multi-lines for better reading.) 1: node fetch.js 2: "http://www.igt.com/us-en.aspx" 3: "http://www.igt.com/us-en/games.aspx" 4: "http://www.igt.com/us-en/cabinets.aspx" 5: "http://www.igt.com/us-en/systems.aspx" 6: "http://www.igt.com/us-en/interactive.aspx" 7: "http://www.igt.com/us-en/social-gaming.aspx" 8: "http://www.igt.com/support.aspx" Below is the output. As you can see the finish message was printed at the beginning, and the pages’ length retrieved in a different order than we specified. This is because in this code the request command, console logging command are executed asynchronously and concurrently. Now let’s introduce “Wind” to make them executed in order, which means it will request the websites one by one, and print the message at the end.   First of all we need to import the “Wind” package and make sure the there’s only one global variant named “Wind”, and ensure it’s “Wind” instead of “wind”. 1: var Wind = require("wind");   Next, we need to tell “Wind” which code will be executed asynchronously so that “Wind” can control the execution process. In this case the “request” operation executed asynchronously so we will create a “Task” by using a build-in helps function in “Wind” named Wind.Async.Task.create. 1: var requestBodyLengthAsync = function(url) { 2: return Wind.Async.Task.create(function(t) { 3: request(url, function(error, response, body) { 4: if(error || response.statusCode != 200) { 5: t.complete("failure", error); 6: } 7: else { 8: var data = 9: { 10: uri: response.request.uri.href, 11: length: body.length 12: }; 13: t.complete("success", data); 14: } 15: }); 16: }); 17: }; The code above created a “Task” from the original request calling code. In “Wind” a “Task” means an operation will be finished in some time in the future. A “Task” can be started by invoke its start() method, but no one knows when it actually will be finished. The Wind.Async.Task.create helped us to create a task. The only parameter is a function where we can put the actual operation in, and then notify the task object it’s finished successfully or failed by using the complete() method. In the code above I invoked the request method. If it retrieved the response successfully I set the status of this task as “success” with the URL and body length. If it failed I set this task as “failure” and pass the error out.   Next, we will change the main() function. In “Wind” if we want a function can be controlled by Wind we need to mark it as “async”. This should be done by using the code below. 1: var main = eval(Wind.compile("async", function() { 2: })); When the application is running, Wind will detect “eval(Wind.compile(“async”, function” and generate an anonymous code from the body of this original function. Then the application will run the anonymous code instead of the original one. In our example the main function will be like this. 1: var main = eval(Wind.compile("async", function() { 2: for(var i = 0; i < args.length; i++) { 3: try 4: { 5: var result = $await(requestBodyLengthAsync(args[i])); 6: console.log( 7: "%s: %d.", 8: result.uri, 9: result.length); 10: } 11: catch (ex) { 12: console.log(ex); 13: } 14: } 15: 16: console.log("Finished"); 17: })); As you can see, when I tried to request the URL I use a new command named “$await”. It tells Wind, the operation next to $await will be executed asynchronously, and the main thread should be paused until it finished (or failed). So in this case, my application will be pause when the first response was received, and then print its body length, then try the next one. At the end, print the finish message.   Finally, execute the main function. The full code would be like this. 1: var request = require("request"); 2: var Wind = require("wind"); 3:  4: var args = process.argv.splice(2); 5:  6: var requestBodyLengthAsync = function(url) { 7: return Wind.Async.Task.create(function(t) { 8: request(url, function(error, response, body) { 9: if(error || response.statusCode != 200) { 10: t.complete("failure", error); 11: } 12: else { 13: var data = 14: { 15: uri: response.request.uri.href, 16: length: body.length 17: }; 18: t.complete("success", data); 19: } 20: }); 21: }); 22: }; 23:  24: var main = eval(Wind.compile("async", function() { 25: for(var i = 0; i < args.length; i++) { 26: try 27: { 28: var result = $await(requestBodyLengthAsync(args[i])); 29: console.log( 30: "%s: %d.", 31: result.uri, 32: result.length); 33: } 34: catch (ex) { 35: console.log(ex); 36: } 37: } 38: 39: console.log("Finished"); 40: })); 41:  42: main().start();   Run our new application. At the beginning we will see the compiled and generated code by Wind. Then we can see the pages were requested one by one, and at the end the finish message was printed. Below is the code Wind generated for us. As you can see the original code, the output code were shown. 1: // Original: 2: function () { 3: for(var i = 0; i < args.length; i++) { 4: try 5: { 6: var result = $await(requestBodyLengthAsync(args[i])); 7: console.log( 8: "%s: %d.", 9: result.uri, 10: result.length); 11: } 12: catch (ex) { 13: console.log(ex); 14: } 15: } 16: 17: console.log("Finished"); 18: } 19:  20: // Compiled: 21: /* async << function () { */ (function () { 22: var _builder_$0 = Wind.builders["async"]; 23: return _builder_$0.Start(this, 24: _builder_$0.Combine( 25: _builder_$0.Delay(function () { 26: /* var i = 0; */ var i = 0; 27: /* for ( */ return _builder_$0.For(function () { 28: /* ; i < args.length */ return i < args.length; 29: }, function () { 30: /* ; i ++) { */ i ++; 31: }, 32: /* try { */ _builder_$0.Try( 33: _builder_$0.Delay(function () { 34: /* var result = $await(requestBodyLengthAsync(args[i])); */ return _builder_$0.Bind(requestBodyLengthAsync(args[i]), function (result) { 35: /* console.log("%s: %d.", result.uri, result.length); */ console.log("%s: %d.", result.uri, result.length); 36: return _builder_$0.Normal(); 37: }); 38: }), 39: /* } catch (ex) { */ function (ex) { 40: /* console.log(ex); */ console.log(ex); 41: return _builder_$0.Normal(); 42: /* } */ }, 43: null 44: ) 45: /* } */ ); 46: }), 47: _builder_$0.Delay(function () { 48: /* console.log("Finished"); */ console.log("Finished"); 49: return _builder_$0.Normal(); 50: }) 51: ) 52: ); 53: /* } */ })   How Wind Works Someone may raise a big concern when you find I utilized “eval” in my code. Someone may assume that Wind utilizes “eval” to execute some code dynamically while “eval” is very low performance. But I would say, Wind does NOT use “eval” to run the code. It only use “eval” as a flag to know which code should be compiled at runtime. When the code was firstly been executed, Wind will check and find “eval(Wind.compile(“async”, function”. So that it knows this function should be compiled. Then it utilized parse-js to analyze the inner JavaScript and generated the anonymous code in memory. Then it rewrite the original code so that when the application was running it will use the anonymous one instead of the original one. Since the code generation was done at the beginning of the application was started, in the future no matter how long our application runs and how many times the async function was invoked, it will use the generated code, no need to generate again. So there’s no significant performance hurt when using Wind.   Wind in My Previous Demo Let’s adopt Wind into one of my previous demonstration and to see how it helps us to make our code simple, straightforward and easy to read and understand. In this post when I implemented the functionality that copied the records from my WASD to table storage, the logic would be like this. 1, Open database connection. 2, Execute a query to select all records from the table. 3, Recreate the table in Windows Azure table storage. 4, Create entities from each of the records retrieved previously, and then insert them into table storage. 5, Finally, show message as the HTTP response. But as the image below, since there are so many callbacks and async operations, it’s very hard to understand my logic from the code. Now let’s use Wind to rewrite our code. First of all, of course, we need the Wind package. Then we need to include the package files into project and mark them as “Copy always”. Add the Wind package into the source code. Pay attention to the variant name, you must use “Wind” instead of “wind”. 1: var express = require("express"); 2: var async = require("async"); 3: var sql = require("node-sqlserver"); 4: var azure = require("azure"); 5: var Wind = require("wind"); Now we need to create some async functions by using Wind. All async functions should be wrapped so that it can be controlled by Wind which are open database, retrieve records, recreate table (delete and create) and insert entity in table. Below are these new functions. All of them are created by using Wind.Async.Task.create. 1: sql.openAsync = function (connectionString) { 2: return Wind.Async.Task.create(function (t) { 3: sql.open(connectionString, function (error, conn) { 4: if (error) { 5: t.complete("failure", error); 6: } 7: else { 8: t.complete("success", conn); 9: } 10: }); 11: }); 12: }; 13:  14: sql.queryAsync = function (conn, query) { 15: return Wind.Async.Task.create(function (t) { 16: conn.queryRaw(query, function (error, results) { 17: if (error) { 18: t.complete("failure", error); 19: } 20: else { 21: t.complete("success", results); 22: } 23: }); 24: }); 25: }; 26:  27: azure.recreateTableAsync = function (tableName) { 28: return Wind.Async.Task.create(function (t) { 29: client.deleteTable(tableName, function (error, successful, response) { 30: console.log("delete table finished"); 31: client.createTableIfNotExists(tableName, function (error, successful, response) { 32: console.log("create table finished"); 33: if (error) { 34: t.complete("failure", error); 35: } 36: else { 37: t.complete("success", null); 38: } 39: }); 40: }); 41: }); 42: }; 43:  44: azure.insertEntityAsync = function (tableName, entity) { 45: return Wind.Async.Task.create(function (t) { 46: client.insertEntity(tableName, entity, function (error, entity, response) { 47: if (error) { 48: t.complete("failure", error); 49: } 50: else { 51: t.complete("success", null); 52: } 53: }); 54: }); 55: }; Then in order to use these functions we will create a new function which contains all steps for data copying. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: } 4: catch (ex) { 5: console.log(ex); 6: res.send(500, "Internal error."); 7: } 8: })); Let’s execute steps one by one with the “$await” keyword introduced by Wind so that it will be invoked in sequence. First is to open the database connection. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: } 7: catch (ex) { 8: console.log(ex); 9: res.send(500, "Internal error."); 10: } 11: })); Then retrieve all records from the database connection. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: // retrieve all records from database 7: var results = $await(sql.queryAsync(conn, "SELECT * FROM [Resource]")); 8: console.log("records selected. count = %d", results.rows.length); 9: } 10: catch (ex) { 11: console.log(ex); 12: res.send(500, "Internal error."); 13: } 14: })); After recreated the table, we need to create the entities and insert them into table storage. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: // retrieve all records from database 7: var results = $await(sql.queryAsync(conn, "SELECT * FROM [Resource]")); 8: console.log("records selected. count = %d", results.rows.length); 9: if (results.rows.length > 0) { 10: // recreate the table 11: $await(azure.recreateTableAsync(tableName)); 12: console.log("table created"); 13: // insert records in table storage one by one 14: for (var i = 0; i < results.rows.length; i++) { 15: var entity = { 16: "PartitionKey": results.rows[i][1], 17: "RowKey": results.rows[i][0], 18: "Value": results.rows[i][2] 19: }; 20: $await(azure.insertEntityAsync(tableName, entity)); 21: console.log("entity inserted"); 22: } 23: } 24: } 25: catch (ex) { 26: console.log(ex); 27: res.send(500, "Internal error."); 28: } 29: })); Finally, send response back to the browser. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: // retrieve all records from database 7: var results = $await(sql.queryAsync(conn, "SELECT * FROM [Resource]")); 8: console.log("records selected. count = %d", results.rows.length); 9: if (results.rows.length > 0) { 10: // recreate the table 11: $await(azure.recreateTableAsync(tableName)); 12: console.log("table created"); 13: // insert records in table storage one by one 14: for (var i = 0; i < results.rows.length; i++) { 15: var entity = { 16: "PartitionKey": results.rows[i][1], 17: "RowKey": results.rows[i][0], 18: "Value": results.rows[i][2] 19: }; 20: $await(azure.insertEntityAsync(tableName, entity)); 21: console.log("entity inserted"); 22: } 23: // send response 24: console.log("all done"); 25: res.send(200, "All done!"); 26: } 27: } 28: catch (ex) { 29: console.log(ex); 30: res.send(500, "Internal error."); 31: } 32: })); If we compared with the previous code we will find now it became more readable and much easy to understand. It’s very easy to know what this function does even though without any comments. When user go to URL “/was/copyRecords” we will execute the function above. The code would be like this. 1: app.get("/was/copyRecords", function (req, res) { 2: copyRecords(req, res).start(); 3: }); And below is the logs printed in local compute emulator console. As we can see the functions executed one by one and then finally the response back to me browser.   Scaffold Functions in Wind Wind provides not only the async flow control and compile functions, but many scaffold methods as well. We can build our async code more easily by using them. I’m going to introduce some basic scaffold functions here. In the code above I created some functions which wrapped from the original async function such as open database, create table, etc.. All of them are very similar, created a task by using Wind.Async.Task.create, return error or result object through Task.complete function. In fact, Wind provides some functions for us to create task object from the original async functions. If the original async function only has a callback parameter, we can use Wind.Async.Binding.fromCallback method to get the task object directly. For example the code below returned the task object which wrapped the file exist check function. 1: var Wind = require("wind"); 2: var fs = require("fs"); 3:  4: fs.existsAsync = Wind.Async.Binding.fromCallback(fs.exists); In Node.js a very popular async function pattern is that, the first parameter in the callback function represent the error object, and the other parameters is the return values. In this case we can use another build-in function in Wind named Wind.Async.Binding.fromStandard. For example, the open database function can be created from the code below. 1: sql.openAsync = Wind.Async.Binding.fromStandard(sql.open); 2:  3: /* 4: sql.openAsync = function (connectionString) { 5: return Wind.Async.Task.create(function (t) { 6: sql.open(connectionString, function (error, conn) { 7: if (error) { 8: t.complete("failure", error); 9: } 10: else { 11: t.complete("success", conn); 12: } 13: }); 14: }); 15: }; 16: */ When I was testing the scaffold functions under Wind.Async.Binding I found for some functions, such as the Azure SDK insert entity function, cannot be processed correctly. So I personally suggest writing the wrapped method manually.   Another scaffold method in Wind is the parallel tasks coordination. In this example, the steps of open database, retrieve records and recreated table should be invoked one by one, but it can be executed in parallel when copying data from database to table storage. In Wind there’s a scaffold function named Task.whenAll which can be used here. Task.whenAll accepts a list of tasks and creates a new task. It will be returned only when all tasks had been completed, or any errors occurred. For example in the code below I used the Task.whenAll to make all copy operation executed at the same time. 1: var copyRecordsInParallel = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: // retrieve all records from database 7: var results = $await(sql.queryAsync(conn, "SELECT * FROM [Resource]")); 8: console.log("records selected. count = %d", results.rows.length); 9: if (results.rows.length > 0) { 10: // recreate the table 11: $await(azure.recreateTableAsync(tableName)); 12: console.log("table created"); 13: // insert records in table storage in parallal 14: var tasks = new Array(results.rows.length); 15: for (var i = 0; i < results.rows.length; i++) { 16: var entity = { 17: "PartitionKey": results.rows[i][1], 18: "RowKey": results.rows[i][0], 19: "Value": results.rows[i][2] 20: }; 21: tasks[i] = azure.insertEntityAsync(tableName, entity); 22: } 23: $await(Wind.Async.Task.whenAll(tasks)); 24: // send response 25: console.log("all done"); 26: res.send(200, "All done!"); 27: } 28: } 29: catch (ex) { 30: console.log(ex); 31: res.send(500, "Internal error."); 32: } 33: })); 34:  35: app.get("/was/copyRecordsInParallel", function (req, res) { 36: copyRecordsInParallel(req, res).start(); 37: });   Besides the task creation and coordination, Wind supports the cancellation solution so that we can send the cancellation signal to the tasks. It also includes exception solution which means any exceptions will be reported to the caller function.   Summary In this post I introduced a Node.js module named Wind, which created by my friend Jeff Zhao. As you can see, different from other async library and framework, adopted the idea from F# and C#, Wind utilizes runtime code generation technology to make it more easily to write async, callback-based functions in a sync-style way. By using Wind there will be almost no callback, and the code will be very easy to understand. Currently Wind is still under developed and improved. There might be some problems but the author, Jeff, should be very happy and enthusiastic to learn your problems, feedback, suggestion and comments. You can contact Jeff by - Email: [email protected] - Group: https://groups.google.com/d/forum/windjs - GitHub: https://github.com/JeffreyZhao/wind/issues   Source code can be download here.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • urlencode an array of values

    - by Ikke
    I'm trying to urlencode an dictionary in python with urllib.urlencode. The problem is, I have to encode an array. The result needs to be: criterias%5B%5D=member&criterias%5B%5D=issue #unquoted: criterias[]=member&criterias[]=issue But the result I get is: criterias=%5B%27member%27%2C+%27issue%27%5D #unquoted: criterias=['member',+'issue'] I have tried several things, but I can't seem to get the right result. import urllib criterias = ['member', 'issue'] params = { 'criterias[]': criterias, } print urllib.urlencode(params) If I use cgi.parse_qs to decode a correct query string, I get this as result: {'criterias[]': ['member', 'issue']} But if I encode that result, I get a wrong result back. Is there a way to produce the expected result?

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  • simple c# arythmetics. winForms

    - by jello
    I'm doing simple divisions in c#, and I am a bit puzzled by its intricacies. Here's some code, and in the comments, the result. (btw, I only compile with 1 line not commented, if you say that I have 5 declarations of the same variable) double result = 2 / 3; //gives 0 double result = Convert.ToDouble(2) / Convert.ToDouble(3); // is good double result = double.Parse(2) / double.Parse(3); // gives me errors double result = double.Parse(2 / 3); // gives me errors double result = Convert.ToDouble(2 / 3); // gives 0 MessageBox.Show(result.ToString()); so if you have a bunch of integers you wanna mess with, you have to convert each one to a double. pretty tedious...

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  • simple c# arithmetics. winForms

    - by jello
    I'm doing simple divisions in c#, and I am a bit puzzled by its intricacies. Here's some code, and in the comments, the result. (btw, I only compile with 1 line not commented, if you say that I have 5 declarations of the same variable) double result = 2 / 3; //gives 0 double result = Convert.ToDouble(2) / Convert.ToDouble(3); // is good double result = double.Parse(2) / double.Parse(3); // gives me errors double result = double.Parse(2 / 3); // gives me errors double result = Convert.ToDouble(2 / 3); // gives 0 MessageBox.Show(result.ToString()); so if you have a bunch of integers you wanna mess with, you have to convert each one to a double. pretty tedious...

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  • Trying to reduce the speed overhead of an almost-but-not-quite-int number class

    - by Fumiyo Eda
    I have implemented a C++ class which behaves very similarly to the standard int type. The difference is that it has an additional concept of "epsilon" which represents some tiny value that is much less than 1, but greater than 0. One way to think of it is as a very wide fixed point number with 32 MSBs (the integer parts), 32 LSBs (the epsilon parts) and a huge sea of zeros in between. The following class works, but introduces a ~2x speed penalty in the overall program. (The program includes code that has nothing to do with this class, so the actual speed penalty of this class is probably much greater than 2x.) I can't paste the code that is using this class, but I can say the following: +, -, +=, <, > and >= are the only heavily used operators. Use of setEpsilon() and getInt() is extremely rare. * is also rare, and does not even need to consider the epsilon values at all. Here is the class: #include <limits> struct int32Uepsilon { typedef int32Uepsilon Self; int32Uepsilon () { _value = 0; _eps = 0; } int32Uepsilon (const int &i) { _value = i; _eps = 0; } void setEpsilon() { _eps = 1; } Self operator+(const Self &rhs) const { Self result = *this; result._value += rhs._value; result._eps += rhs._eps; return result; } Self operator-(const Self &rhs) const { Self result = *this; result._value -= rhs._value; result._eps -= rhs._eps; return result; } Self operator-( ) const { Self result = *this; result._value = -result._value; result._eps = -result._eps; return result; } Self operator*(const Self &rhs) const { return this->getInt() * rhs.getInt(); } // XXX: discards epsilon bool operator<(const Self &rhs) const { return (_value < rhs._value) || (_value == rhs._value && _eps < rhs._eps); } bool operator>(const Self &rhs) const { return (_value > rhs._value) || (_value == rhs._value && _eps > rhs._eps); } bool operator>=(const Self &rhs) const { return (_value >= rhs._value) || (_value == rhs._value && _eps >= rhs._eps); } Self &operator+=(const Self &rhs) { this->_value += rhs._value; this->_eps += rhs._eps; return *this; } Self &operator-=(const Self &rhs) { this->_value -= rhs._value; this->_eps -= rhs._eps; return *this; } int getInt() const { return(_value); } private: int _value; int _eps; }; namespace std { template<> struct numeric_limits<int32Uepsilon> { static const bool is_signed = true; static int max() { return 2147483647; } } }; The code above works, but it is quite slow. Does anyone have any ideas on how to improve performance? There are a few hints/details I can give that might be helpful: 32 bits are definitely insufficient to hold both _value and _eps. In practice, up to 24 ~ 28 bits of _value are used and up to 20 bits of _eps are used. I could not measure a significant performance difference between using int32_t and int64_t, so memory overhead itself is probably not the problem here. Saturating addition/subtraction on _eps would be cool, but isn't really necessary. Note that the signs of _value and _eps are not necessarily the same! This broke my first attempt at speeding this class up. Inline assembly is no problem, so long as it works with GCC on a Core i7 system running Linux!

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  • Use filter(), but work with both results

    - by Tomalak
    In jQuery, filter() reduces your result to those elements that fulfill a certain condition. This splits the list in two parts. Working with the "good half" of the elements is easy: $("some selector").filter(function() { // determine result... return result; }).each( /* do something */ ); But how can I work with the "other half" of my elements, too - but without doing the equivalent of this: $("some selector").filter(function() { // determine result... return !result; }).each( /* do something else */ ); Basically, I'd like to feed two separate /* do something */ parts to a single filter. One for those that match, and one for the others - without having to filter twice. Am I missing a jQuery function that does this? P.S.: I guess I could do: $("some selector").each(function() { // determine result... if (result) /* do something */ else /* do something else */ }); But I was hoping for something nicer.

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  • losing leading & trailing space when translated using Google Machine Translation

    - by Sourabh
    Hi , I am using google ajax based translation API like in the below example. google.load("language", "1"); function initialize() { var text = document.getElementById("text").innerHTML; google.language.detect(text, function(result) { if (!result.error && result.language) { google.language.translate(text, result.language, "en", function(result) { var translated = document.getElementById("translation"); if (result.translation) { translated.innerHTML = result.translation; } }); } }); } google.setOnLoadCallback(initialize); When I send string like " how are you? " The transaltion what I get is like "xxx xxx xxxxxxx" . the spaces in the original string are trimmed.How do I prevent it from happening ?

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  • Embedded C++, any tips to avoid a local thats only used to return a value on the stack?

    - by lisarc
    I have a local that's only used for the purposes of checking the result from another function and passing it on if it meets certain criteria. Most of the time, that criteria will never be met. Is there any way I can avoid this "extra" local? I only have about 1MB of storage for my binary, and I have several thousand function calls that follow this pattern. I know it's a minor thing, but if there's a better pattern I'd love to know! SomeDataType myclass::myFunction() { SomeDataType result; // do I really need this local??? // i need to check the result and pass it on if it meets a certain condition result = doSomething(); if ( ! result ) { return result; } // do other things here ... // normal result of processing return SomeDataType(whatever); }

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  • Making uppercase of std::string

    - by Daniel K.
    Which implementation do you think is better? std::string ToUpper( const std::string& source ) { std::string result; result.reserve( source.length() ); std::transform( source.begin(), source.end(), result.begin(), std::ptr_fun<int, int>( std::toupper ) ); return result; } and... std::string ToUpper( const std::string& source ) { std::string result( source.length(), '\0' ); std::transform( source.begin(), source.end(), result.begin(), std::ptr_fun<int, int>( std::toupper ) ); return result; } Difference is that the first one uses reserve method after the default constructor, but the second one uses the constructor accepting the number of characters.

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