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  • MySQL: LIMIT then RAND rather than RAND then LIMIT

    - by Larry
    I'm using full text search to pull rows. I order the rows based on score (ORDER BY SCORE) , then of the top 20 rows (LIMIT 20), I want to rand (RAND) the result set. So for any specific search term, I want to randomly show 5 of the top 20 results. My workaround is code based- where I put the top 20 into an array then randomly select 5. Is there sql way to do this?

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  • LIMIT then RAND rather than RAND then LIMIT

    - by Larry
    I'm using full text search to pull rows. I order the rows based on score (ORDER BY SCORE) , then of the top 20 rows (LIMIT 20), I want to rand (RAND) the result set. So for any specific search term, I want to randomly show 5 of the top 20 results. My workaround is code based- where I put the top 20 into an array then randomly select 5. Is there sql way to do this?

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  • Linux buffer cache effect on IO writes?

    - by Patrick LeBoutillier
    I'm copying large files (3 x 30G) between 2 filesystems on a Linux server (kernel 2.6.37, 16 cores, 32G RAM) and I'm getting poor performance. I suspect that the usage of the buffer cache is killing the I/O performance. To try and narrow down the problem I used fio directly on the SAS disk to monitor the performance. Here is the output of 2 fio runs (the first with direct=1, the second one direct=0): Config: [test] rw=write blocksize=32k size=20G filename=/dev/sda # direct=1 Run 1: test: (g=0): rw=write, bs=32K-32K/32K-32K, ioengine=sync, iodepth=1 Starting 1 process Jobs: 1 (f=1): [W] [100.0% done] [0K/205M /s] [0/6K iops] [eta 00m:00s] test: (groupid=0, jobs=1): err= 0: pid=4667 write: io=20,480MB, bw=199MB/s, iops=6,381, runt=102698msec clat (usec): min=104, max=13,388, avg=152.06, stdev=72.43 bw (KB/s) : min=192448, max=213824, per=100.01%, avg=204232.82, stdev=4084.67 cpu : usr=3.37%, sys=16.55%, ctx=655410, majf=0, minf=29 IO depths : 1=100.0%, 2=0.0%, 4=0.0%, 8=0.0%, 16=0.0%, 32=0.0%, >=64=0.0% submit : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.0%, 64=0.0%, >=64=0.0% complete : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.0%, 64=0.0%, >=64=0.0% issued r/w: total=0/655360, short=0/0 lat (usec): 250=99.50%, 500=0.45%, 750=0.01%, 1000=0.01% lat (msec): 2=0.01%, 4=0.02%, 10=0.01%, 20=0.01% Run status group 0 (all jobs): WRITE: io=20,480MB, aggrb=199MB/s, minb=204MB/s, maxb=204MB/s, mint=102698msec, maxt=102698msec Disk stats (read/write): sda: ios=0/655238, merge=0/0, ticks=0/79552, in_queue=78640, util=76.55% Run 2: test: (g=0): rw=write, bs=32K-32K/32K-32K, ioengine=sync, iodepth=1 Starting 1 process Jobs: 1 (f=1): [W] [100.0% done] [0K/0K /s] [0/0 iops] [eta 00m:00s] test: (groupid=0, jobs=1): err= 0: pid=4733 write: io=20,480MB, bw=91,265KB/s, iops=2,852, runt=229786msec clat (usec): min=16, max=127K, avg=349.53, stdev=4694.98 bw (KB/s) : min=56013, max=1390016, per=101.47%, avg=92607.31, stdev=167453.17 cpu : usr=0.41%, sys=6.93%, ctx=21128, majf=0, minf=33 IO depths : 1=100.0%, 2=0.0%, 4=0.0%, 8=0.0%, 16=0.0%, 32=0.0%, >=64=0.0% submit : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.0%, 64=0.0%, >=64=0.0% complete : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.0%, 64=0.0%, >=64=0.0% issued r/w: total=0/655360, short=0/0 lat (usec): 20=5.53%, 50=93.89%, 100=0.02%, 250=0.01%, 500=0.01% lat (msec): 2=0.01%, 4=0.01%, 10=0.01%, 20=0.01%, 50=0.12% lat (msec): 100=0.38%, 250=0.04% Run status group 0 (all jobs): WRITE: io=20,480MB, aggrb=91,265KB/s, minb=93,455KB/s, maxb=93,455KB/s, mint=229786msec, maxt=229786msec Disk stats (read/write): sda: ios=8/79811, merge=7/7721388, ticks=9/32418456, in_queue=32471983, util=98.98% I'm not knowledgeable enough with fio to interpret the results, but I don't expect the overall performance using the buffer cache to be 50% less than with O_DIRECT. Can someone help me interpret the fio output? Are there any kernel tunings that could fix/minimize the problem? Thanks a lot,

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  • abstract data type list. . .

    - by aldrin
    A LIST is an ordered collection of items where items may be inserted anywhere in the list. Implement a LIST using an array as follows: struct list { int *items; // pointer to the array int size; // actual size of the array int count; // number of items in the array }; typedef struct list *List; // pointer to the structure Implement the following functions: a) List newList(int size); - will create a new List and return its pointer. Allocate space for the structure, allocate space for the array, then initialize size and count, return the pointer. b) void isEmpty(List list); c) void display(List list); d) int contains(List list, int item); e) void remove(List list, int i) ; f) void insertAfter(List list,int item, int i); g) void addEnd(List list,int item) - add item at the end of the list – simply store the data at position count, then increment count. If the array is full, allocate an array twice as big as the original. count = 5 size = 10 0 1 2 3 4 5 6 7 8 9 5 10 15 20 30 addEnd(list,40) will result to count = 6 size = 10 0 1 2 3 4 5 6 7 8 9 5 10 15 20 30 40 h) void addFront(List list,int item) - shift all elements to the right so that the item can be placed at position 0, then increment count. Bonus: if the array is full, allocate an array twice as big as the original. count = 5 size = 10 0 1 2 3 4 5 6 7 8 9 5 10 15 20 30 addFront(list,40) will result to count = 6 size = 10 0 1 2 3 4 5 6 7 8 9 40 5 10 15 20 30 i) void removeFront(List list) - shift all elements to the left and decrement count; count = 6 size = 10 0 1 2 3 4 5 6 7 8 9 40 5 10 15 20 30 removeFront(list) will result to count = 5 size = 10 0 1 2 3 4 5 6 7 8 9 5 10 15 20 30 j) void remove(List list,int item) - get the index of the item in the list and then shift all elements to the count = 6 size = 10 0 1 2 3 4 5 6 7 8 9 40 5 10 15 20 30 remove(list,10) will result to count = 5 size = 10 0 1 2 3 4 5 6 7 8 9 40 5 15 20 30

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  • Linux buffer cache effect on IO writes?

    - by Patrick LeBoutillier
    Hi, I'm copying large files (3 x 30G) between 2 filesystems on a Linux server (kernel 2.6.37, 16 cores, 32G RAM) and I'm getting poor performance. I suspect that the usage of the buffer cache is killing the I/O performance. To try and narrow down the problem I used fio directly on the SAS disk to monitor the performance. Here is the output of 2 fio runs (the first with direct=1, the second one direct=0): Config: [test] rw=write blocksize=32k size=20G filename=/dev/sda # direct=1 Run 1: test: (g=0): rw=write, bs=32K-32K/32K-32K, ioengine=sync, iodepth=1 Starting 1 process Jobs: 1 (f=1): [W] [100.0% done] [0K/205M /s] [0/6K iops] [eta 00m:00s] test: (groupid=0, jobs=1): err= 0: pid=4667 write: io=20,480MB, bw=199MB/s, iops=6,381, runt=102698msec clat (usec): min=104, max=13,388, avg=152.06, stdev=72.43 bw (KB/s) : min=192448, max=213824, per=100.01%, avg=204232.82, stdev=4084.67 cpu : usr=3.37%, sys=16.55%, ctx=655410, majf=0, minf=29 IO depths : 1=100.0%, 2=0.0%, 4=0.0%, 8=0.0%, 16=0.0%, 32=0.0%, >=64=0.0% submit : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.0%, 64=0.0%, >=64=0.0% complete : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.0%, 64=0.0%, >=64=0.0% issued r/w: total=0/655360, short=0/0 lat (usec): 250=99.50%, 500=0.45%, 750=0.01%, 1000=0.01% lat (msec): 2=0.01%, 4=0.02%, 10=0.01%, 20=0.01% Run status group 0 (all jobs): WRITE: io=20,480MB, aggrb=199MB/s, minb=204MB/s, maxb=204MB/s, mint=102698msec, maxt=102698msec Disk stats (read/write): sda: ios=0/655238, merge=0/0, ticks=0/79552, in_queue=78640, util=76.55% Run 2: test: (g=0): rw=write, bs=32K-32K/32K-32K, ioengine=sync, iodepth=1 Starting 1 process Jobs: 1 (f=1): [W] [100.0% done] [0K/0K /s] [0/0 iops] [eta 00m:00s] test: (groupid=0, jobs=1): err= 0: pid=4733 write: io=20,480MB, bw=91,265KB/s, iops=2,852, runt=229786msec clat (usec): min=16, max=127K, avg=349.53, stdev=4694.98 bw (KB/s) : min=56013, max=1390016, per=101.47%, avg=92607.31, stdev=167453.17 cpu : usr=0.41%, sys=6.93%, ctx=21128, majf=0, minf=33 IO depths : 1=100.0%, 2=0.0%, 4=0.0%, 8=0.0%, 16=0.0%, 32=0.0%, >=64=0.0% submit : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.0%, 64=0.0%, >=64=0.0% complete : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.0%, 64=0.0%, >=64=0.0% issued r/w: total=0/655360, short=0/0 lat (usec): 20=5.53%, 50=93.89%, 100=0.02%, 250=0.01%, 500=0.01% lat (msec): 2=0.01%, 4=0.01%, 10=0.01%, 20=0.01%, 50=0.12% lat (msec): 100=0.38%, 250=0.04% Run status group 0 (all jobs): WRITE: io=20,480MB, aggrb=91,265KB/s, minb=93,455KB/s, maxb=93,455KB/s, mint=229786msec, maxt=229786msec Disk stats (read/write): sda: ios=8/79811, merge=7/7721388, ticks=9/32418456, in_queue=32471983, util=98.98% I'm not knowledgeable enough with fio to interpret the results, but I don't expect the overall performance using the buffer cache to be 50% less than with O_DIRECT. Can someone help me interpret the fio output? Are there any kernel tunings that could fix/minimize the problem? Thanks a lot,

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  • How to connect to a Virtualbox guest from the host when network cable unplugged

    - by Greg K
    I'd like to work offline (I'm flying to the US twice this month), to do this I need access to a linux development server. When I work from home I boot a VirtualBox VM and that acts as my dev server for the day (providing Apache, PHP & MySQL to run my server side code). However, I'd like to work with my VM when I'm not connected to a network. I have my Ubuntu VM guest set up with a bridge connection so it can serve HTTP and provide SSH access from inside my local network. I've tried to manually configure my network settings on both Mac OSX (the host) and Ubuntu (the guest) but I can't even ping my own NIC address (127.0.0.1 can, 192.168.21.x I can't) in OS X when I unplug the cable. Manual network settings: $ ifconfig en0 en0: flags=8963<UP,BROADCAST,SMART,RUNNING,PROMISC,SIMPLEX,MULTICAST> mtu 1500 ether 00:xx:xx:xx:xx:xx inet 192.168.21.5 netmask 0xffffff00 broadcast 192.168.21.255 media: autoselect (100baseTX <full-duplex,flow-control>) status: active I can ping localhost fine, as well as my VM (.20) and SSH too. $ ping 192.168.21.5 PING 192.168.21.5 (192.168.21.5): 56 data bytes 64 bytes from 192.168.21.5: icmp_seq=0 ttl=64 time=0.085 ms 64 bytes from 192.168.21.5: icmp_seq=1 ttl=64 time=0.102 ms 64 bytes from 192.168.21.5: icmp_seq=2 ttl=64 time=0.100 ms 64 bytes from 192.168.21.5: icmp_seq=3 ttl=64 time=0.094 ms $ ping 192.168.21.20 PING 192.168.21.20 (192.168.21.20): 56 data bytes 64 bytes from 192.168.21.20: icmp_seq=0 ttl=64 time=0.910 ms 64 bytes from 192.168.21.20: icmp_seq=1 ttl=64 time=1.181 ms 64 bytes from 192.168.21.20: icmp_seq=2 ttl=64 time=1.159 ms 64 bytes from 192.168.21.20: icmp_seq=3 ttl=64 time=1.320 ms Network cable unplugged: $ ifconfig en0 en0: flags=8963<UP,BROADCAST,SMART,RUNNING,PROMISC,SIMPLEX,MULTICAST> mtu 1500 ether 00:xx:xx:xx:xx:xx media: autoselect status: inactive $ ping 192.168.21.5 PING 192.168.21.5 (192.168.21.5): 56 data bytes ping: sendto: No route to host ping: sendto: No route to host Request timeout for icmp_seq 0 ping: sendto: No route to host Request timeout for icmp_seq 1 Does OS X disable the NIC when the network cable is unplugged? Any way to stop it doing this?

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  • invalid effective address calculation!

    - by Zia ur Rahman
    Hay Dear! Please look at the following program, the error is invalid effective address calculation and i have mentioned that line please tell me why its invalid effective address calculation here is the program [org 0x100] jmp start array1: dw 10,15,20,25,30,35,40,45,50,55 array2: dw 15,10,20,35,40,30,55,50,25,45 start: mov bx,0 mov dx,0 loop: mov ax,[array2+bx] cmp ax,[array1+cx]//here is the error invalid effective address calculation jne NextElementOfArray1 NextElementOfArray2: add bx,2 cmp bx,20 je end mov cx,0 jmp loop NextElementOfArray1: add cx,2 cmp cx,20 je NextElementOfArray2 jmp loop end: mov ax,0x4c00 int 0x21

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  • mySQL - How to select a date interval

    - by fabriciols
    Hello, this is my table : ------------------------------------- | user | item | date_time | | 10 | 01 | 10-10-10 20:10:05 | | 10 | 02 | 10-10-10 20:10:10 | | 10 | 03 | 10-10-10 20:10:10 | | 20 | 02 | 10-10-10 20:15:10 | | 20 | 02 | 10-10-10 20:20:10 | | 30 | 10 | 10-10-10 20:01:10 | | 30 | 20 | 10-10-10 20:01:20 | | 30 | 30 | 10-10-10 20:05:20 | ------------------------------------- i want to do a query that return a user that took multiple items in a 1min interval, like this result : ------------------------------------- | user | item | date_time | | 10 | 01 | 10-10-10 20:10:05 | | 10 | 02 | 10-10-10 20:10:10 | | 10 | 03 | 10-10-10 20:10:10 | | 30 | 10 | 10-10-10 20:01:10 | | 30 | 20 | 10-10-10 20:01:20 | ------------------------------------- how i do this ?

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  • How to get the last element by date of each "type" in LINQ or TSQL

    - by Mauro
    Imagine to have a table defined as CREATE TABLE [dbo].[Price]( [ID] [int] NOT NULL, [StartDate] [datetime] NOT NULL, [Price] [int] NOT NULL ) where ID is the identifier of an action having a certain Price. This price can be updated if necessary by adding a new line with the same ID, different Price, and a more recent date. So with a set of a data like ID StartDate Price 1 01/01/2009 10 1 01/01/2010 20 2 01/01/2009 10 2 01/01/2010 20 How to obtain a set like the following? 1 01/01/2010 20 2 01/01/2010 20

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  • Using Qt CSS to set own Q_PROPERTY(QFont)

    - by Kamil Klimek
    Hi there. I'm using Qt 4.6.2 and i have problem with QCSS. I have own Q_PROPERTY(QFont myFont READ myFont SET setMyFont). I want to change it with QCSS but it doesn't work. I've tried using normal font syntax but it doesn't work. I've also tried few other combinations like: qproperty-myFont: font(serif 20 1 0) font(serif 20 bold) QFont(serif 20 1 0) QFont(serif 20 bold) QFont(bold 20px serif) etc.

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  • Abstract Data Type: Any1 can help me this? thanks..

    - by Aga Hibaya
    Objectives: Implement the Abstract Data Type (ADT) List using dynamically allocated arrays and structures. Description A LIST is an ordered collection of items where items may be inserted anywhere in the list. Implement a LIST using an array as follows: struct list { int *items; // pointer to the array int size; // actual size of the array int count; // number of items in the array }; typedef struct list *List; // pointer to the structure Implement the following functions: a) List newList(int size); - will create a new List and return its pointer. Allocate space for the structure, allocate space for the array, then initialize size and count, return the pointer. b) void isEmpty(List list); c) void display(List list); d) int contains(List list, int item); e) void remove(List list, int i) ; f) void insertAfter(List list,int item, int i); g) void addEnd(List list,int item) - add item at the end of the list – simply store the data at position count, then increment count. If the array is full, allocate an array twice as big as the original. count = 5 size = 10 0 1 2 3 4 5 6 7 8 9 5 10 15 20 30 addEnd(list,40) will result to count = 6 size = 10 0 1 2 3 4 5 6 7 8 9 5 10 15 20 30 40 h) void addFront(List list,int item) - shift all elements to the right so that the item can be placed at position 0, then increment count. Bonus: if the array is full, allocate an array twice as big as the original. count = 5 size = 10 0 1 2 3 4 5 6 7 8 9 5 10 15 20 30 addFront(list,40) will result to count = 6 size = 10 0 1 2 3 4 5 6 7 8 9 40 5 10 15 20 30 i) void removeFront(List list) - shift all elements to the left and decrement count; count = 6 size = 10 0 1 2 3 4 5 6 7 8 9 40 5 10 15 20 30 removeFront(list) will result to count = 5 size = 10 0 1 2 3 4 5 6 7 8 9 5 10 15 20 30 j) void remove(List list,int item) - get the index of the item in the list and then shift all elements to the count = 6 size = 10 0 1 2 3 4 5 6 7 8 9 40 5 10 15 20 30 remove(list,10) will result to count = 5 size = 10 0 1 2 3 4 5 6 7 8 9 40 5 15 20 30 Remarks

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  • SSH Socks Proxy wiith iptables REDIRECT

    - by Radium
    I have googled and haven`t found the answer on my question. Help me please. There are two servers: serverA with public IP 12.0.0.10 and an private IP 10.0.0.5 serverB with public IP 20.0.0.11 I have setup SOCKS proxy on serverB to serverA: ssh -D20.0.0.11:2222 [email protected] So when on my local machine in a browser i specify SOCKS proxy 20.0.0.11:2222 (serverB:2222) as external IP while browsing i get 12.0.0.10 (serverA IP). That is ok. As well if i go onto http://10.0.0.5 (serverA private IP) it is also reachable. That is what i need. I want to make servers A private IP to be available through servers B public IP on certain ports but without specifying SOCKS in my browser. I could use ssh port forward but the problem is - i need to forward many ports and do not know which exactly - i know only the range. So when i connect to 20.0.0.11 to any port , for example, from 3000:4000 range, i want that traffic to be redirected to 10.0.0.5 on the same port. That is why i`ve decided maybe SOCKS proxy via SSH and iptables REDIRECT could help me. Client - serverBPublicIP (any port from range 3000:4000) - serverAPublicIP - serverAPrivateIP (the port was requested on serverBPublicIP) On serverB i do: ssh -D20.0.0.11:2222 [email protected] iptables -t nat -A PREROUTING -d 20.0.0.11 -p tcp --dport 3000:4000 -j REDIRECT --to-port 2222 But that does not work - when i telnet on 20.0.0.11:3001 for example i do not see any proxied traffic on the serverA. What should i do else? I have tried tcpsocks like this (in example i am telneting to 20.0.0.11:3001) Client -> 20.0.0.11:3001 -> iptables REDIRECT from 3001 --to-port 1111 -> tcpsocks from 1111 to 2222 -> SOCKS proxy from serverB to serverA on port 2222 -> serverA But i do not know what to do with the traffic on serverA. How to route it to its private IP. Help me please. I know, VPN removes all the hell i am trying to create, but i have no ability to use tun/tap device. It is disabled.

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  • looping through a 2d array in ruby to display it in a table format?

    - by Sean
    Hi How can i represent a 2d array in a table format in the terminal, where it lines up the columns properly just like a table? so it looks like so: 1 2 3 4 5 1 [ Infinity | 40 | 45 | Infinity | Infinity ] 2 [ Infinity | 20 | 50 | 14 | 20 ] 3 [ Infinity | 30 | 40 | Infinity | 40 ] 4 [ Infinity | 28 | Infinity | 6 | 6 ] 5 [ Infinity | 40 | 80 | 12 | 0 ] instead of: [ Infinity,40,45,Infinity,Infinity ] [ Infinity,20,50,14,20 ] [ Infinity,30,40,Infinity,40 ] [ Infinity,28,Infinity,6,6 ] [ Infinity,40,80,12,0 ]

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  • mysql display each day in a month

    - by Jason
    during a month, display the infor each date, order by date, but this infor is empty in some day. how can i still display each day as a row? Product date ----------------- 20 2008-01-01 10 2008-01-02 20 2008-01-03 10 2008-01-05 09 2008-01-08 30 2008-01-09 result: Product date ----------------- 20 2008-01-01 10 2008-01-02 20 2008-01-03 0 2008-01-04 10 2008-01-05 0 2008-01-06 0 2008-01-07 09 2008-01-08 30 2008-01-09

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  • How to parse date from html page using html agility pack ?

    - by Harikrishna
    I have html pages and I am parsing those pages with html agility pack. Now I want to parse some information.In every pages there is trading date(20/02/02) which I want to parse. Like it will be look like a Trading date : 20/02/02. Now Trading date and date(20/02/02) may be in same column(td) or it can be different column like in first column trading date and in second column 20/02/02 then what should I do ?

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  • t-sql get variable value from string with variable name

    - by Markus
    Hi. Is there a way to convert '@my_variable' string into a value of @my_variable? I have a table which stores names of variables. I need to get the value of this variable. Something like this: DECLARE @second_variable AS NVARCHAR(20); DECLARE @first_variable AS NVARCHAR(20); SET @first_variable = '20'; SET @second_variable = SELECT '@first_variable'; --here I want that @second variable be assigned a value of "20".

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  • which images load the android device at the time of installation?

    - by VSC
    I am placing 20 images in hdpi folder, 20 images in mdpi folder and 20 images in ldpi folder, all are same images but different resolutions . I am placing my app in android market. One user install my app in his normal android device through market, My question is total 60 images download the device or only 20 images(mdpi) download the device at the time of install the app.Thanks for reading my question.

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  • Upload File to Windows Azure Blob in Chunks through ASP.NET MVC, JavaScript and HTML5

    - by Shaun
    Originally posted on: http://geekswithblogs.net/shaunxu/archive/2013/07/01/upload-file-to-windows-azure-blob-in-chunks-through-asp.net.aspxMany people are using Windows Azure Blob Storage to store their data in the cloud. Blob storage provides 99.9% availability with easy-to-use API through .NET SDK and HTTP REST. For example, we can store JavaScript files, images, documents in blob storage when we are building an ASP.NET web application on a Web Role in Windows Azure. Or we can store our VHD files in blob and mount it as a hard drive in our cloud service. If you are familiar with Windows Azure, you should know that there are two kinds of blob: page blob and block blob. The page blob is optimized for random read and write, which is very useful when you need to store VHD files. The block blob is optimized for sequential/chunk read and write, which has more common usage. Since we can upload block blob in blocks through BlockBlob.PutBlock, and them commit them as a whole blob with invoking the BlockBlob.PutBlockList, it is very powerful to upload large files, as we can upload blocks in parallel, and provide pause-resume feature. There are many documents, articles and blog posts described on how to upload a block blob. Most of them are focus on the server side, which means when you had received a big file, stream or binaries, how to upload them into blob storage in blocks through .NET SDK.  But the problem is, how can we upload these large files from client side, for example, a browser. This questioned to me when I was working with a Chinese customer to help them build a network disk production on top of azure. The end users upload their files from the web portal, and then the files will be stored in blob storage from the Web Role. My goal is to find the best way to transform the file from client (end user’s machine) to the server (Web Role) through browser. In this post I will demonstrate and describe what I had done, to upload large file in chunks with high speed, and save them as blocks into Windows Azure Blob Storage.   Traditional Upload, Works with Limitation The simplest way to implement this requirement is to create a web page with a form that contains a file input element and a submit button. 1: @using (Html.BeginForm("About", "Index", FormMethod.Post, new { enctype = "multipart/form-data" })) 2: { 3: <input type="file" name="file" /> 4: <input type="submit" value="upload" /> 5: } And then in the backend controller, we retrieve the whole content of this file and upload it in to the blob storage through .NET SDK. We can split the file in blocks and upload them in parallel and commit. The code had been well blogged in the community. 1: [HttpPost] 2: public ActionResult About(HttpPostedFileBase file) 3: { 4: var container = _client.GetContainerReference("test"); 5: container.CreateIfNotExists(); 6: var blob = container.GetBlockBlobReference(file.FileName); 7: var blockDataList = new Dictionary<string, byte[]>(); 8: using (var stream = file.InputStream) 9: { 10: var blockSizeInKB = 1024; 11: var offset = 0; 12: var index = 0; 13: while (offset < stream.Length) 14: { 15: var readLength = Math.Min(1024 * blockSizeInKB, (int)stream.Length - offset); 16: var blockData = new byte[readLength]; 17: offset += stream.Read(blockData, 0, readLength); 18: blockDataList.Add(Convert.ToBase64String(BitConverter.GetBytes(index)), blockData); 19:  20: index++; 21: } 22: } 23:  24: Parallel.ForEach(blockDataList, (bi) => 25: { 26: blob.PutBlock(bi.Key, new MemoryStream(bi.Value), null); 27: }); 28: blob.PutBlockList(blockDataList.Select(b => b.Key).ToArray()); 29:  30: return RedirectToAction("About"); 31: } This works perfect if we selected an image, a music or a small video to upload. But if I selected a large file, let’s say a 6GB HD-movie, after upload for about few minutes the page will be shown as below and the upload will be terminated. In ASP.NET there is a limitation of request length and the maximized request length is defined in the web.config file. It’s a number which less than about 4GB. So if we want to upload a really big file, we cannot simply implement in this way. Also, in Windows Azure, a cloud service network load balancer will terminate the connection if exceed the timeout period. From my test the timeout looks like 2 - 3 minutes. Hence, when we need to upload a large file we cannot just use the basic HTML elements. Besides the limitation mentioned above, the simple HTML file upload cannot provide rich upload experience such as chunk upload, pause and pause-resume. So we need to find a better way to upload large file from the client to the server.   Upload in Chunks through HTML5 and JavaScript In order to break those limitation mentioned above we will try to upload the large file in chunks. This takes some benefit to us such as - No request size limitation: Since we upload in chunks, we can define the request size for each chunks regardless how big the entire file is. - No timeout problem: The size of chunks are controlled by us, which means we should be able to make sure request for each chunk upload will not exceed the timeout period of both ASP.NET and Windows Azure load balancer. It was a big challenge to upload big file in chunks until we have HTML5. There are some new features and improvements introduced in HTML5 and we will use them to implement our solution.   In HTML5, the File interface had been improved with a new method called “slice”. It can be used to read part of the file by specifying the start byte index and the end byte index. For example if the entire file was 1024 bytes, file.slice(512, 768) will read the part of this file from the 512nd byte to 768th byte, and return a new object of interface called "Blob”, which you can treat as an array of bytes. In fact,  a Blob object represents a file-like object of immutable, raw data. The File interface is based on Blob, inheriting blob functionality and expanding it to support files on the user's system. For more information about the Blob please refer here. File and Blob is very useful to implement the chunk upload. We will use File interface to represent the file the user selected from the browser and then use File.slice to read the file in chunks in the size we wanted. For example, if we wanted to upload a 10MB file with 512KB chunks, then we can read it in 512KB blobs by using File.slice in a loop.   Assuming we have a web page as below. User can select a file, an input box to specify the block size in KB and a button to start upload. 1: <div> 2: <input type="file" id="upload_files" name="files[]" /><br /> 3: Block Size: <input type="number" id="block_size" value="512" name="block_size" />KB<br /> 4: <input type="button" id="upload_button_blob" name="upload" value="upload (blob)" /> 5: </div> Then we can have the JavaScript function to upload the file in chunks when user clicked the button. 1: <script type="text/javascript"> 1: 2: $(function () { 3: $("#upload_button_blob").click(function () { 4: }); 5: });</script> Firstly we need to ensure the client browser supports the interfaces we are going to use. Just try to invoke the File, Blob and FormData from the “window” object. If any of them is “undefined” the condition result will be “false” which means your browser doesn’t support these premium feature and it’s time for you to get your browser updated. FormData is another new feature we are going to use in the future. It could generate a temporary form for us. We will use this interface to create a form with chunk and associated metadata when invoked the service through ajax. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: if (window.File && window.Blob && window.FormData) { 4: alert("Your brwoser is awesome, let's rock!"); 5: } 6: else { 7: alert("Oh man plz update to a modern browser before try is cool stuff out."); 8: return; 9: } 10: }); Each browser supports these interfaces by their own implementation and currently the Blob, File and File.slice are supported by Chrome 21, FireFox 13, IE 10, Opera 12 and Safari 5.1 or higher. After that we worked on the files the user selected one by one since in HTML5, user can select multiple files in one file input box. 1: var files = $("#upload_files")[0].files; 2: for (var i = 0; i < files.length; i++) { 3: var file = files[i]; 4: var fileSize = file.size; 5: var fileName = file.name; 6: } Next, we calculated the start index and end index for each chunks based on the size the user specified from the browser. We put them into an array with the file name and the index, which will be used when we upload chunks into Windows Azure Blob Storage as blocks since we need to specify the target blob name and the block index. At the same time we will store the list of all indexes into another variant which will be used to commit blocks into blob in Azure Storage once all chunks had been uploaded successfully. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10:  11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: var blockSizeInKB = $("#block_size").val(); 14: var blockSize = blockSizeInKB * 1024; 15: var blocks = []; 16: var offset = 0; 17: var index = 0; 18: var list = ""; 19: while (offset < fileSize) { 20: var start = offset; 21: var end = Math.min(offset + blockSize, fileSize); 22:  23: blocks.push({ 24: name: fileName, 25: index: index, 26: start: start, 27: end: end 28: }); 29: list += index + ","; 30:  31: offset = end; 32: index++; 33: } 34: } 35: }); Now we have all chunks’ information ready. The next step should be upload them one by one to the server side, and at the server side when received a chunk it will upload as a block into Blob Storage, and finally commit them with the index list through BlockBlobClient.PutBlockList. But since all these invokes are ajax calling, which means not synchronized call. So we need to introduce a new JavaScript library to help us coordinate the asynchronize operation, which named “async.js”. You can download this JavaScript library here, and you can find the document here. I will not explain this library too much in this post. We will put all procedures we want to execute as a function array, and pass into the proper function defined in async.js to let it help us to control the execution sequence, in series or in parallel. Hence we will define an array and put the function for chunk upload into this array. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4:  5: // start to upload each files in chunks 6: var files = $("#upload_files")[0].files; 7: for (var i = 0; i < files.length; i++) { 8: var file = files[i]; 9: var fileSize = file.size; 10: var fileName = file.name; 11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: ... ... 14:  15: // define the function array and push all chunk upload operation into this array 16: blocks.forEach(function (block) { 17: putBlocks.push(function (callback) { 18: }); 19: }); 20: } 21: }); 22: }); As you can see, I used File.slice method to read each chunks based on the start and end byte index we calculated previously, and constructed a temporary HTML form with the file name, chunk index and chunk data through another new feature in HTML5 named FormData. Then post this form to the backend server through jQuery.ajax. This is the key part of our solution. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: blocks.forEach(function (block) { 15: putBlocks.push(function (callback) { 16: // load blob based on the start and end index for each chunks 17: var blob = file.slice(block.start, block.end); 18: // put the file name, index and blob into a temporary from 19: var fd = new FormData(); 20: fd.append("name", block.name); 21: fd.append("index", block.index); 22: fd.append("file", blob); 23: // post the form to backend service (asp.net mvc controller action) 24: $.ajax({ 25: url: "/Home/UploadInFormData", 26: data: fd, 27: processData: false, 28: contentType: "multipart/form-data", 29: type: "POST", 30: success: function (result) { 31: if (!result.success) { 32: alert(result.error); 33: } 34: callback(null, block.index); 35: } 36: }); 37: }); 38: }); 39: } 40: }); Then we will invoke these functions one by one by using the async.js. And once all functions had been executed successfully I invoked another ajax call to the backend service to commit all these chunks (blocks) as the blob in Windows Azure Storage. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.series(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); That’s all in the client side. The outline of our logic would be - Calculate the start and end byte index for each chunks based on the block size. - Defined the functions of reading the chunk form file and upload the content to the backend service through ajax. - Execute the functions defined in previous step with “async.js”. - Commit the chunks by invoking the backend service in Windows Azure Storage finally.   Save Chunks as Blocks into Blob Storage In above we finished the client size JavaScript code. It uploaded the file in chunks to the backend service which we are going to implement in this step. We will use ASP.NET MVC as our backend service, and it will receive the chunks, upload into Windows Azure Bob Storage in blocks, then finally commit as one blob. As in the client side we uploaded chunks by invoking the ajax call to the URL "/Home/UploadInFormData", I created a new action under the Index controller and it only accepts HTTP POST request. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: } 8: catch (Exception e) 9: { 10: error = e.ToString(); 11: } 12:  13: return new JsonResult() 14: { 15: Data = new 16: { 17: success = string.IsNullOrWhiteSpace(error), 18: error = error 19: } 20: }; 21: } Then I retrieved the file name, index and the chunk content from the Request.Form object, which was passed from our client side. And then, used the Windows Azure SDK to create a blob container (in this case we will use the container named “test”.) and create a blob reference with the blob name (same as the file name). Then uploaded the chunk as a block of this blob with the index, since in Blob Storage each block must have an index (ID) associated with so that finally we can put all blocks as one blob by specifying their block ID list. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var index = int.Parse(Request.Form["index"]); 9: var file = Request.Files[0]; 10: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 11:  12: var container = _client.GetContainerReference("test"); 13: container.CreateIfNotExists(); 14: var blob = container.GetBlockBlobReference(name); 15: blob.PutBlock(id, file.InputStream, null); 16: } 17: catch (Exception e) 18: { 19: error = e.ToString(); 20: } 21:  22: return new JsonResult() 23: { 24: Data = new 25: { 26: success = string.IsNullOrWhiteSpace(error), 27: error = error 28: } 29: }; 30: } Next, I created another action to commit the blocks into blob once all chunks had been uploaded. Similarly, I retrieved the blob name from the Request.Form. I also retrieved the chunks ID list, which is the block ID list from the Request.Form in a string format, split them as a list, then invoked the BlockBlob.PutBlockList method. After that our blob will be shown in the container and ready to be download. 1: [HttpPost] 2: public JsonResult Commit() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var list = Request.Form["list"]; 9: var ids = list 10: .Split(',') 11: .Where(id => !string.IsNullOrWhiteSpace(id)) 12: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 13: .ToArray(); 14:  15: var container = _client.GetContainerReference("test"); 16: container.CreateIfNotExists(); 17: var blob = container.GetBlockBlobReference(name); 18: blob.PutBlockList(ids); 19: } 20: catch (Exception e) 21: { 22: error = e.ToString(); 23: } 24:  25: return new JsonResult() 26: { 27: Data = new 28: { 29: success = string.IsNullOrWhiteSpace(error), 30: error = error 31: } 32: }; 33: } Now we finished all code we need. The whole process of uploading would be like this below. Below is the full client side JavaScript code. 1: <script type="text/javascript" src="~/Scripts/async.js"></script> 2: <script type="text/javascript"> 3: $(function () { 4: $("#upload_button_blob").click(function () { 5: // assert the browser support html5 6: if (window.File && window.Blob && window.FormData) { 7: alert("Your brwoser is awesome, let's rock!"); 8: } 9: else { 10: alert("Oh man plz update to a modern browser before try is cool stuff out."); 11: return; 12: } 13:  14: // start to upload each files in chunks 15: var files = $("#upload_files")[0].files; 16: for (var i = 0; i < files.length; i++) { 17: var file = files[i]; 18: var fileSize = file.size; 19: var fileName = file.name; 20:  21: // calculate the start and end byte index for each blocks(chunks) 22: // with the index, file name and index list for future using 23: var blockSizeInKB = $("#block_size").val(); 24: var blockSize = blockSizeInKB * 1024; 25: var blocks = []; 26: var offset = 0; 27: var index = 0; 28: var list = ""; 29: while (offset < fileSize) { 30: var start = offset; 31: var end = Math.min(offset + blockSize, fileSize); 32:  33: blocks.push({ 34: name: fileName, 35: index: index, 36: start: start, 37: end: end 38: }); 39: list += index + ","; 40:  41: offset = end; 42: index++; 43: } 44:  45: // define the function array and push all chunk upload operation into this array 46: var putBlocks = []; 47: blocks.forEach(function (block) { 48: putBlocks.push(function (callback) { 49: // load blob based on the start and end index for each chunks 50: var blob = file.slice(block.start, block.end); 51: // put the file name, index and blob into a temporary from 52: var fd = new FormData(); 53: fd.append("name", block.name); 54: fd.append("index", block.index); 55: fd.append("file", blob); 56: // post the form to backend service (asp.net mvc controller action) 57: $.ajax({ 58: url: "/Home/UploadInFormData", 59: data: fd, 60: processData: false, 61: contentType: "multipart/form-data", 62: type: "POST", 63: success: function (result) { 64: if (!result.success) { 65: alert(result.error); 66: } 67: callback(null, block.index); 68: } 69: }); 70: }); 71: }); 72:  73: // invoke the functions one by one 74: // then invoke the commit ajax call to put blocks into blob in azure storage 75: async.series(putBlocks, function (error, result) { 76: var data = { 77: name: fileName, 78: list: list 79: }; 80: $.post("/Home/Commit", data, function (result) { 81: if (!result.success) { 82: alert(result.error); 83: } 84: else { 85: alert("done!"); 86: } 87: }); 88: }); 89: } 90: }); 91: }); 92: </script> And below is the full ASP.NET MVC controller code. 1: public class HomeController : Controller 2: { 3: private CloudStorageAccount _account; 4: private CloudBlobClient _client; 5:  6: public HomeController() 7: : base() 8: { 9: _account = CloudStorageAccount.Parse(CloudConfigurationManager.GetSetting("DataConnectionString")); 10: _client = _account.CreateCloudBlobClient(); 11: } 12:  13: public ActionResult Index() 14: { 15: ViewBag.Message = "Modify this template to jump-start your ASP.NET MVC application."; 16:  17: return View(); 18: } 19:  20: [HttpPost] 21: public JsonResult UploadInFormData() 22: { 23: var error = string.Empty; 24: try 25: { 26: var name = Request.Form["name"]; 27: var index = int.Parse(Request.Form["index"]); 28: var file = Request.Files[0]; 29: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 30:  31: var container = _client.GetContainerReference("test"); 32: container.CreateIfNotExists(); 33: var blob = container.GetBlockBlobReference(name); 34: blob.PutBlock(id, file.InputStream, null); 35: } 36: catch (Exception e) 37: { 38: error = e.ToString(); 39: } 40:  41: return new JsonResult() 42: { 43: Data = new 44: { 45: success = string.IsNullOrWhiteSpace(error), 46: error = error 47: } 48: }; 49: } 50:  51: [HttpPost] 52: public JsonResult Commit() 53: { 54: var error = string.Empty; 55: try 56: { 57: var name = Request.Form["name"]; 58: var list = Request.Form["list"]; 59: var ids = list 60: .Split(',') 61: .Where(id => !string.IsNullOrWhiteSpace(id)) 62: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 63: .ToArray(); 64:  65: var container = _client.GetContainerReference("test"); 66: container.CreateIfNotExists(); 67: var blob = container.GetBlockBlobReference(name); 68: blob.PutBlockList(ids); 69: } 70: catch (Exception e) 71: { 72: error = e.ToString(); 73: } 74:  75: return new JsonResult() 76: { 77: Data = new 78: { 79: success = string.IsNullOrWhiteSpace(error), 80: error = error 81: } 82: }; 83: } 84: } And if we selected a file from the browser we will see our application will upload chunks in the size we specified to the server through ajax call in background, and then commit all chunks in one blob. Then we can find the blob in our Windows Azure Blob Storage.   Optimized by Parallel Upload In previous example we just uploaded our file in chunks. This solved the problem that ASP.NET MVC request content size limitation as well as the Windows Azure load balancer timeout. But it might introduce the performance problem since we uploaded chunks in sequence. In order to improve the upload performance we could modify our client side code a bit to make the upload operation invoked in parallel. The good news is that, “async.js” library provides the parallel execution function. If you remembered the code we invoke the service to upload chunks, it utilized “async.series” which means all functions will be executed in sequence. Now we will change this code to “async.parallel”. This will invoke all functions in parallel. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallel(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); In this way all chunks will be uploaded to the server side at the same time to maximize the bandwidth usage. This should work if the file was not very large and the chunk size was not very small. But for large file this might introduce another problem that too many ajax calls are sent to the server at the same time. So the best solution should be, upload the chunks in parallel with maximum concurrency limitation. The code below specified the concurrency limitation to 4, which means at the most only 4 ajax calls could be invoked at the same time. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallelLimit(putBlocks, 4, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: });   Summary In this post we discussed how to upload files in chunks to the backend service and then upload them into Windows Azure Blob Storage in blocks. We focused on the frontend side and leverage three new feature introduced in HTML 5 which are - File.slice: Read part of the file by specifying the start and end byte index. - Blob: File-like interface which contains the part of the file content. - FormData: Temporary form element that we can pass the chunk alone with some metadata to the backend service. Then we discussed the performance consideration of chunk uploading. Sequence upload cannot provide maximized upload speed, but the unlimited parallel upload might crash the browser and server if too many chunks. So we finally came up with the solution to upload chunks in parallel with the concurrency limitation. We also demonstrated how to utilize “async.js” JavaScript library to help us control the asynchronize call and the parallel limitation.   Regarding the chunk size and the parallel limitation value there is no “best” value. You need to test vary composition and find out the best one for your particular scenario. It depends on the local bandwidth, client machine cores and the server side (Windows Azure Cloud Service Virtual Machine) cores, memory and bandwidth. Below is one of my performance test result. The client machine was Windows 8 IE 10 with 4 cores. I was using Microsoft Cooperation Network. The web site was hosted on Windows Azure China North data center (in Beijing) with one small web role (1.7GB 1 core CPU, 1.75GB memory with 100Mbps bandwidth). The test cases were - Chunk size: 512KB, 1MB, 2MB, 4MB. - Upload Mode: Sequence, parallel (unlimited), parallel with limit (4 threads, 8 threads). - Chunk Format: base64 string, binaries. - Target file: 100MB. - Each case was tested 3 times. Below is the test result chart. Some thoughts, but not guidance or best practice: - Parallel gets better performance than series. - No significant performance improvement between parallel 4 threads and 8 threads. - Transform with binaries provides better performance than base64. - In all cases, chunk size in 1MB - 2MB gets better performance.   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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  • Building an interleaved buffer for pyopengl and numpy

    - by Nick Sonneveld
    I'm trying to batch up a bunch of vertices and texture coords in an interleaved array before sending it to pyOpengl's glInterleavedArrays/glDrawArrays. The only problem is that I'm unable to find a suitably fast enough way to append data into a numpy array. Is there a better way to do this? I would have thought it would be quicker to preallocate the array and then fill it with data but instead, generating a python list and converting it to a numpy array is "faster". Although 15ms for 4096 quads seems slow. I have included some example code and their timings. #!/usr/bin/python import timeit import numpy import ctypes import random USE_RANDOM=True USE_STATIC_BUFFER=True STATIC_BUFFER = numpy.empty(4096*20, dtype=numpy.float32) def render(i): # pretend these are different each time if USE_RANDOM: tex_left, tex_right, tex_top, tex_bottom = random.random(), random.random(), random.random(), random.random() left, right, top, bottom = random.random(), random.random(), random.random(), random.random() else: tex_left, tex_right, tex_top, tex_bottom = 0.0, 1.0, 1.0, 0.0 left, right, top, bottom = -1.0, 1.0, 1.0, -1.0 ibuffer = ( tex_left, tex_bottom, left, bottom, 0.0, # Lower left corner tex_right, tex_bottom, right, bottom, 0.0, # Lower right corner tex_right, tex_top, right, top, 0.0, # Upper right corner tex_left, tex_top, left, top, 0.0, # upper left ) return ibuffer # create python list.. convert to numpy array at end def create_array_1(): ibuffer = [] for x in xrange(4096): data = render(x) ibuffer += data ibuffer = numpy.array(ibuffer, dtype=numpy.float32) return ibuffer # numpy.array, placing individually by index def create_array_2(): if USE_STATIC_BUFFER: ibuffer = STATIC_BUFFER else: ibuffer = numpy.empty(4096*20, dtype=numpy.float32) index = 0 for x in xrange(4096): data = render(x) for v in data: ibuffer[index] = v index += 1 return ibuffer # using slicing def create_array_3(): if USE_STATIC_BUFFER: ibuffer = STATIC_BUFFER else: ibuffer = numpy.empty(4096*20, dtype=numpy.float32) index = 0 for x in xrange(4096): data = render(x) ibuffer[index:index+20] = data index += 20 return ibuffer # using numpy.concat on a list of ibuffers def create_array_4(): ibuffer_concat = [] for x in xrange(4096): data = render(x) # converting makes a diff! data = numpy.array(data, dtype=numpy.float32) ibuffer_concat.append(data) return numpy.concatenate(ibuffer_concat) # using numpy array.put def create_array_5(): if USE_STATIC_BUFFER: ibuffer = STATIC_BUFFER else: ibuffer = numpy.empty(4096*20, dtype=numpy.float32) index = 0 for x in xrange(4096): data = render(x) ibuffer.put( xrange(index, index+20), data) index += 20 return ibuffer # using ctype array CTYPES_ARRAY = ctypes.c_float*(4096*20) def create_array_6(): ibuffer = [] for x in xrange(4096): data = render(x) ibuffer += data ibuffer = CTYPES_ARRAY(*ibuffer) return ibuffer def equals(a, b): for i,v in enumerate(a): if b[i] != v: return False return True if __name__ == "__main__": number = 100 # if random, don't try and compare arrays if not USE_RANDOM and not USE_STATIC_BUFFER: a = create_array_1() assert equals( a, create_array_2() ) assert equals( a, create_array_3() ) assert equals( a, create_array_4() ) assert equals( a, create_array_5() ) assert equals( a, create_array_6() ) t = timeit.Timer( "testing2.create_array_1()", "import testing2" ) print 'from list:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_2()", "import testing2" ) print 'array: indexed:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_3()", "import testing2" ) print 'array: slicing:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_4()", "import testing2" ) print 'array: concat:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_5()", "import testing2" ) print 'array: put:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_6()", "import testing2" ) print 'ctypes float array:', t.timeit(number)/number*1000.0, 'ms' Timings using random numbers: $ python testing2.py from list: 15.0486779213 ms array: indexed: 24.8184704781 ms array: slicing: 50.2214789391 ms array: concat: 44.1691994667 ms array: put: 73.5879898071 ms ctypes float array: 20.6674289703 ms edit note: changed code to produce random numbers for each render to reduce object reuse and to simulate different vertices each time. edit note2: added static buffer and force all numpy.empty() to use dtype=float32 note 1/Apr/2010: still no progress and I don't really feel that any of the answers have solved the problem yet.

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  • Background changes by itself and procedure repeats many times until I release the mouse button

    - by Robert
    Dear community, I am a student, and I'm working on a little slots game (if the same random number comes up 3 timed, you win). I use Borland Pascal 7. I use graph to make this a bit more visual, but when I start the game my background turns from black to grey, and the other problem is that if I click the game start button, the game runs many times until I release the mouse button. How can I solve this? Here is my full program: program slots; uses mymouse,graph,crt; var gdriver,gmode,coin:integer; m:mouserec; a,b,c,coins:string; procedure gomb(x1,y1,x2,y2:integer;szoveg:string); var j,n:integer; begin setcolor(blue); rectangle(x1,y1,x2,y2); setfillstyle(1,blue); floodfill(x1+2,y1+2,blue); setcolor(0); outtextxy((x1+x2)div 2 -textwidth(szoveg) div 2 ,(y1+y2) div 2-textheight(szoveg) div 2,szoveg); end; procedure randomal(var a,b,c:string); begin randomize; STR(random(2)+1,a); STR(random(2)+1,b); STR(random(2)+1,c); end; procedure menu; begin; settextstyle(0,0,1); outtextxy(20,10,'Meno menu'); gomb(20,20,90,50,'Teglalap'); gomb(20,60,90,90,'Inditas'); gomb(20,100,90,130,'Harmadik'); gomb(20,140,90,170,'Negyedik'); end; procedure teglalap(x1,x2,y1,y2,tinta:integer); begin setcolor(tinta); rectangle(x1,x2,y1,y2); end; procedure jatek(var a,b,c:string;var coin:integer;coins:string); begin; clrscr; menu; randomal(a,b,c); if ((a=b) AND (b=c)) then coin:=coin+1 else coin:=coin-1; settextstyle(0,0,3); setbkcolor(black); outtextxy(200,20,a); outtextxy(240,20,b); outtextxy(280,20,c); STR(coin,coins); outtextxy(400,400,coins); end; procedure eger; begin; mouseinit; mouseon; menu; repeat getmouse(m); if (m.left) and (m.x20) ANd (m.x<90) and (m.y20) and (m.y<50) then teglalap(90,90,300,300,blue); if (m.left) and (m.x20) AND (m.x<90) and (m.y60) and (m.y<90) then jatek(a,b,c,coin,coins); until ((m.left) and (m.x20) ANd (m.x<140) and (m.y140) and (m.y<170)); end; begin coin:=50; gdriver:=detect; initgraph(gdriver, gmode, ''); eger; end. Thank you very much, Robert

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  • How to query on table returned by Stored procedure within a procedure.

    - by Shantanu Gupta
    I have a stored procedure that is performing some ddl dml operations. It retrieves a data after processing data from CTE and cross apply and other such complex things. Now this returns me a 4 tables which gets binded to various sources at frontend. Now I want to use one of the table to further processing so as to get more usefull information from it. eg. This table would be containing approx 2000 records at most of which i want to get records that belongs to lodging only. PK_CATEGORY_ID DESCRIPTION FK_CATEGORY_ID IMMEDIATE_PARENT Department_ID Department_Name DESCRIPTION_HIERARCHY DEPTH IS_ACTIVE ID_PATH DESC_PATH -------------------- -------------------------------------------------- -------------------- -------------------------------------------------- -------------------- -------------------------------------------------- ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ----------- ----------- ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 1 Food NULL NULL 1 Food (Food) Food 0 1 0 Food 5 Chinese 1 Food 1 Food (Food) ----Chinese 1 1 1 Food->Chinese 14 X 5 Chinese 1 Food (Food) --------X 2 1 1->5 Food->Chinese->X 15 Y 5 Chinese 1 Food (Food) --------Y 2 1 1->5 Food->Chinese->Y 65 asdasd 5 Chinese 1 Food (Food) --------asdasd 2 1 1->5 Food->Chinese->asdasd 66 asdas 5 Chinese 1 Food (Food) --------asdas 2 1 1->5 Food->Chinese->asdas 8 Italian 1 Food 1 Food (Food) ----Italian 1 1 1 Food->Italian 48 hfghfgh 1 Food 1 Food (Food) ----hfghfgh 1 1 1 Food->hfghfgh 55 Asd 1 Food 1 Food (Food) ----Asd 1 1 1 Food->Asd 2 Lodging NULL NULL 2 Lodging (Lodging) Lodging 0 1 0 Lodging 3 Room 2 Lodging 2 Lodging (Lodging) ----Room 1 1 2 Lodging->Room 4 Floor 3 Room 2 Lodging (Lodging) --------Floor 2 1 2->3 Lodging->Room->Floor 9 First 4 Floor 2 Lodging (Lodging) ------------First 3 1 2->3->4 Lodging->Room->Floor->First 10 Second 4 Floor 2 Lodging (Lodging) ------------Second 3 1 2->3->4 Lodging->Room->Floor->Second 11 Third 4 Floor 2 Lodging (Lodging) ------------Third 3 1 2->3->4 Lodging->Room->Floor->Third 29 Fourth 4 Floor 2 Lodging (Lodging) ------------Fourth 3 1 2->3->4 Lodging->Room->Floor->Fourth 12 Air Conditioned 3 Room 2 Lodging (Lodging) --------Air Conditioned 2 1 2->3 Lodging->Room->Air Conditioned 20 With Balcony 12 Air Conditioned 2 Lodging (Lodging) ------------With Balcony 3 1 2->3->12 Lodging->Room->Air Conditioned->With Balcony 24 Mountain View 20 With Balcony 2 Lodging (Lodging) ----------------Mountain View 4 1 2->3->12->20 Lodging->Room->Air Conditioned->With Balcony->Mountain View 25 Ocean View 20 With Balcony 2 Lodging (Lodging) ----------------Ocean View 4 1 2->3->12->20 Lodging->Room->Air Conditioned->With Balcony->Ocean View 26 Garden View 20 With Balcony 2 Lodging (Lodging) ----------------Garden View 4 1 2->3->12->20 Lodging->Room->Air Conditioned->With Balcony->Garden View 52 Smoking 20 With Balcony 2 Lodging (Lodging) ----------------Smoking 4 1 2->3->12->20 Lodging->Room->Air Conditioned->With Balcony->Smoking 21 Without Balcony 12 Air Conditioned 2 Lodging (Lodging) ------------Without Balcony 3 1 2->3->12 Lodging->Room->Air Conditioned->Without Balcony 13 Non Air Conditioned 3 Room 2 Lodging (Lodging) --------Non Air Conditioned 2 1 2->3 Lodging->Room->Non Air Conditioned 22 With Balcony 13 Non Air Conditioned 2 Lodging (Lodging) ------------With Balcony 3 1 2->3->13 Lodging->Room->Non Air Conditioned->With Balcony 71 EA 3 Room 2 Lodging (Lodging) --------EA 2 1 2->3 Lodging->Room->EA 50 Casabellas 2 Lodging 2 Lodging (Lodging) ----Casabellas 1 1 2 Lodging->Casabellas 51 North Beach 50 Casabellas 2 Lodging (Lodging) --------North Beach 2 1 2->50 Lodging->Casabellas->North Beach 40 Fooding NULL NULL 40 Fooding (Fooding) Fooding 0 1 0 Fooding 41 Pizza 40 Fooding 40 Fooding (Fooding) ----Pizza 1 1 40 Fooding->Pizza 45 Onion 41 Pizza 40 Fooding (Fooding) --------Onion 2 1 40->41 Fooding->Pizza->Onion 47 Extra Cheeze 41 Pizza 40 Fooding (Fooding) --------Extra Cheeze 2 1 40->41 Fooding->Pizza->Extra Cheeze 77 Burger 40 Fooding 40 Fooding (Fooding) ----Burger 1 1 40 Fooding->Burger This result is being obtained to me using some stored procedure which contains some DML operations as well. i want something like this select description from exec spName where fk_category_id=5 Remember that this spName is returning me 4 tables of which i want to perform some query on one of the table whose index will be known to me. I dont have to send it to UI before querying further. I am using Sql Server 2008 but would like a compatible solution for 2005 also.

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  • add remove field in java script

    - by rajanikant
    Hi every body. i want to add and remove some html input in javascript i have done for add function . it work properly. but unable to remove. my code is following fields = 1; function addInput() { if (fields != 10) { document.getElementById('text').innerHTML += "<tr><td width='15%' align='left' valign='top' class='subheading'><input type='text' name='date[]' id='date[]' /></td><td width='15%' align='left' valign='top' class='subheading'><input type='text' name='time[]' id='time[]' /></td><td width='20%' align='left' valign='top' class='subheading'><input type='text' name='module[]' id='module[]' /></td><td width='15%' align='left' valign='top' class='subheading'><input type='text' name='organisation[]' id='organisation[]' /></td><td width='20%' align='left' valign='top' class='subheading' nowrap='nowrap'><input type='text' name='category[]' id='category[]' /></td><td width='20%' align='left' valign='top' class='text' nowrap='nowrap'>Add | Remove </td></tr>"; fields += 1; } else { document.getElementById('text').innerHTML += "<br />Only 10 upload fields allowed."; document.form.add.disabled=true; } } fields1=10 function removeInput() { if (fields1 !=1) { document.getElementById('text').innerHTML += ""; fields -= 1; } } and my php function is function addSession() {?> <table cellpadding="5" cellspacing="0" width="100%"> <tr> <td width="10%" align="left" valign="top" colspan="6" bgcolor="#993333" class="heading">Add Session </span></td> </tr><tr class="bgrow"> <td width="10%" align="left" valign="top" class="subheading">Datum </span></td> <td width="20%" align="left" valign="top" class="subheading">Tijd</td> <td width="35%" align="left" valign="top" class="subheading">Module</td> <td width="15%" align="left" valign="top" class="subheading">Organisatie</td> <td width="20%" align="left" valign="top" class="subheading" nowrap="nowrap">Category</td> <td width="20%" align="left" valign="top" class="subheading" nowrap="nowrap">Action</td> </tr> <tr > <td width="15%" align="left" valign="top" class="subheading"><input type="text" name="date_0" id="date_0" /></td> <td width="15%" align="left" valign="top" class="subheading"><input type="text" name="time_0" id="time_0" /></td> <td width="20%" align="left" valign="top" class="subheading"><input type="text" name="module_0" id="module_0" /></td> <td width="15%" align="left" valign="top" class="subheading"><input type="text" name="organisation_o" id="organisation_o" /></td> <td width="20%" align="left" valign="top" class="subheading" nowrap="nowrap"><input type="text" name="cat_0" id="cat_0" /></td> <td width="20%" align="left" valign="top" class="text" nowrap="nowrap"><span onclick="addInput()" class="link">Add</span> | <span onclick="removeInput()" class="link">Remove </span></td> </tr> <tbody id="text"> </tbody> <?php } ?> can any one give me solution?

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  • PHP-MySQL: Arranging rows from seperate tables together/Expression to determine row origin

    - by Koroviev
    I'm new to PHP and have a two part question. I need to take rows from two separate tables, and arrange them in descending order by their date. The rows do not correspond in order or number and have no relationship with each other. ---EDIT--- They each contain updates on a site, one table holds text, links, dates, titles etc. from a blog. The other has titles, links, specifications, etc. from images. I want to arrange some basic information (title, date, small description) in an updates section on the main page of the site, and for it to be in order of date. Merging them into one table and modifying it to suit both types isn't what I'd like to do here, the blog table is Wordpress' standard wp_posts and I don't feel comfortable adding columns to make it suit the image table too. I'm afraid it could clash with upgrading later on and it seems like a clumsy solution (but that doesn't mean I'll object if people here advise me it's the best solution). ------EDIT 2------ Here are the DESCRIBES of each table: mysql> describe images; +---------+--------------+------+-----+-------------------+----------------+ | Field | Type | Null | Key | Default | Extra | +---------+--------------+------+-----+-------------------+----------------+ | id | int(11) | NO | PRI | NULL | auto_increment | | project | varchar(255) | NO | | NULL | | | title | varchar(255) | NO | | NULL | | | time | timestamp | NO | | CURRENT_TIMESTAMP | | | img_url | varchar(255) | NO | | NULL | | | alt_txt | varchar(255) | YES | | NULL | | | text | text | YES | | NULL | | | text_id | int(11) | YES | | NULL | | +---------+--------------+------+-----+-------------------+----------------+ mysql> DESCRIBE wp_posts; +-----------------------+---------------------+------+-----+---------------------+----------------+ | Field | Type | Null | Key | Default | Extra | +-----------------------+---------------------+------+-----+---------------------+----------------+ | ID | bigint(20) unsigned | NO | PRI | NULL | auto_increment | | post_author | bigint(20) unsigned | NO | | 0 | | | post_date | datetime | NO | | 0000-00-00 00:00:00 | | | post_date_gmt | datetime | NO | | 0000-00-00 00:00:00 | | | post_content | longtext | NO | | NULL | | | post_title | text | NO | | NULL | | | post_excerpt | text | NO | | NULL | | | post_status | varchar(20) | NO | | publish | | | comment_status | varchar(20) | NO | | open | | | ping_status | varchar(20) | NO | | open | | | post_password | varchar(20) | NO | | | | | post_name | varchar(200) | NO | MUL | | | | to_ping | text | NO | | NULL | | | pinged | text | NO | | NULL | | | post_modified | datetime | NO | | 0000-00-00 00:00:00 | | | post_modified_gmt | datetime | NO | | 0000-00-00 00:00:00 | | | post_content_filtered | text | NO | | NULL | | | post_parent | bigint(20) unsigned | NO | MUL | 0 | | | guid | varchar(255) | NO | | | | | menu_order | int(11) | NO | | 0 | | | post_type | varchar(20) | NO | MUL | post | | | post_mime_type | varchar(100) | NO | | | | | comment_count | bigint(20) | NO | | 0 | | +-----------------------+---------------------+------+-----+---------------------+----------------+ ---END EDIT--- I can do this easily with a single table like this (I include it here in case I'm using an over-elaborate method without knowing it): $content = mysql_query("SELECT post_title, post_text, post_date FROM posts ORDER BY post_date DESC"); while($row = mysql_fetch_array($content)) { echo $row['post_date'], $row['post_title'], $row['post_text']; } But how is it possible to call both tables into the same array to arrange them correctly? By correctly, I mean that they will intermix their echoed results based on their date. Maybe I'm looking at this from the wrong perspective, and calling them to a single array isn't the answer? Additionally, I need a way to form a conditional expression based on which table they came from, so that rows from table 1 get echoed differently than rows from table 2? I want results from table 1 to be echoed differently (with different strings concatenated around them, I mean) for the purpose of styling them differently than those from table two. And vice versa. I know an if...else statement would work here, but I have no idea how can I write the expression that would determine which table the row is from. All and any help is appreciated, thanks.

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  • How to find if a Item in a ListBox has the focus?

    - by eitan barazani
    I have a List box defined like this: <ListBox x:Name="EmailList" ItemsSource="{Binding MailBoxManager.Inbox.EmailList}" SelectedItem="{Binding SelectedMessage, Mode=TwoWay}" Grid.Row="1"> <ListBox.ItemTemplate> <DataTemplate> <usrctrls:MessageSummary /> </DataTemplate> </ListBox.ItemTemplate> </ListBox> The UserControl is defined like this: <UserControl x:Class="UserControls.MessageSummary" xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml" xmlns:d="http://schemas.microsoft.com/expression/blend/2008" xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" mc:Ignorable="d" d:DesignHeight="300" d:DesignWidth="600"> <UserControl.Resources> </UserControl.Resources> <Grid HorizontalAlignment="Left"> <Grid.ColumnDefinitions> <ColumnDefinition Width="50" /> <ColumnDefinition Width="*" /> </Grid.ColumnDefinitions> <CheckBox Grid.Column="0" VerticalAlignment="Center" /> <Grid Grid.Column="1" Margin="0,0,12,0"> <Grid.RowDefinitions> <RowDefinition /> <RowDefinition /> <RowDefinition /> </Grid.RowDefinitions> <Grid Grid.Row="0" Grid.Column="0" HorizontalAlignment="Stretch"> <Grid.ColumnDefinitions> <ColumnDefinition Width="30" /> <ColumnDefinition Width="*" /> <ColumnDefinition Width="80" /> <ColumnDefinition Width="80" /> </Grid.ColumnDefinitions> <Image x:Name="FlaggedImage" Grid.Column="0" Width="20" Height="10" Margin="0" VerticalAlignment="Center" HorizontalAlignment="Center" Source="/Assets/ico_flagged_white.png" /> <TextBlock x:Name="Sender" Grid.Column="1" Text="{Binding EmailProperties.DisplayFrom}" Style="{StaticResource TextBlock_SenderRowTitle}" HorizontalAlignment="Left" VerticalAlignment="Center" /> <Grid x:Name="ImagesContainer" Grid.Column="2" VerticalAlignment="Center"> <Grid.ColumnDefinitions> <ColumnDefinition Width="*" /> <ColumnDefinition Width="*" /> <ColumnDefinition Width="*" /> <ColumnDefinition Width="*" /> </Grid.ColumnDefinitions> <Image x:Name="ImgImportant" Grid.Column="0" Width="20" Height="20" VerticalAlignment="Center" HorizontalAlignment="Center" Source="ms-appx:///Assets/ico_important_red.png" /> <Image x:Name="ImgFolders" Grid.Column="1" Width="20" Height="20" VerticalAlignment="Center" HorizontalAlignment="Center" Source="ms-appx:///Assets/ico_ico_addtofolder.png" /> <Image x:Name="ImgAttachment" Grid.Column="2" Width="20" Height="20" VerticalAlignment="Center" HorizontalAlignment="Center" Source="ms-appx:///Assets/ico_attachment_lightgray.png" /> <Image x:Name="ImgFlag" Grid.Column="3" Width="20" Height="20" VerticalAlignment="Center" HorizontalAlignment="Center" Source="ms-appx:///Assets/ico_flag.png" /> </Grid> <TextBlock x:Name="Time" Grid.Column="3" Text="{Binding EmailProperties.DateReceived, Converter={StaticResource EmailHeaderTimeConverter}}" TextAlignment="Center" FontSize="16" VerticalAlignment="Center" Margin="0" /> </Grid> <TextBlock Grid.Row="1" Text="{Binding EmailProperties.Subject}" TextTrimming="WordEllipsis" Margin="0,10" /> <TextBlock Grid.Row="2" Text="{Binding EmailProperties.Preview}" TextTrimming="WordEllipsis" /> </Grid> </Grid> The MessageSummary is a UserControl. I would like to bind the foreground color of the Items of the ListBox to whether the item is the one selected in the list box, i.e. I would like the Item's foreground color to be Black if not selected and White if the item is selected. How can it be done? Thanks,

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  • Monitoring SQL Server Agent job run times

    - by okeofs
    Introduction A few months back, I was asked how long a particular nightly process took to run. It was a super question and the one thing that struck me was that there were a plethora of factors affecting the processing time. This said, I developed a query to ascertain process run times, the average nightly run times and applied some KPI’s to the end query. The end goal being to enable me to quickly detect anomalies and processes that are running beyond their normal times. As many of you are aware, most of the necessary data for this type of query, lies within the MSDB database. The core portion of the query is shown below.select sj.name,sh.run_date, sh.run_duration, case when len(sh.run_duration) = 6 then convert(varchar(8),sh.run_duration) when len(sh.run_duration) = 5 then '0' + convert(varchar(8),sh.run_duration) when len(sh.run_duration) = 4 then '00' + convert(varchar(8),sh.run_duration) when len(sh.run_duration) = 3 then '000' + convert(varchar(8),sh.run_duration) when len(sh.run_duration) = 2 then '0000' + convert(varchar(8),sh.run_duration) when len(sh.run_duration) = 1 then '00000' + convert(varchar(8),sh.run_duration) end as tt from dbo.sysjobs sj with (nolock) inner join dbo.sysjobHistory sh with (nolock) on sj.job_id = sh.job_id where sj.name = 'My Agent Job' and [sh.Message] like '%The job%') Run_date and run_duration are obvious fields. The field ‘Name’ is the name of the job that we wish to follow. The only major challenge was that the format of the run duration which was not as ‘user friendly’ as I would have liked. As an example, the run duration 1 hour 10 minutes and 3 seconds would be displayed as 11003; whereas I wanted it to display this in a more user friendly manner as 01:10:03. In order to achieve this effect, we need to add leading zeros to the run_duration based upon the case logic shown above. At this point what we need to do add colons between the hours and minutes and one between the minutes and seconds. To achieve this I nested the query shown above (in purple) within a ‘super’ query. Thus the run time ([Run Time]) is constructed concatenating a series of substrings (See below in Blue). select run_date,substring(convert(varchar(20),tt),1,2) + ':' +substring(convert(varchar(20),tt),3,2) + ':' +substring(convert(varchar(20),tt),5,2) as [run_time] from (select sj.name,sh.run_date, sh.run_duration,case when len(sh.run_duration) = 6 then convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 5 then '0' + convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 4 then '00' + convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 3 then '000' + convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 2 then '0000' + convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 1 then '00000' + convert(varchar(8),sh.run_duration)end as ttfrom dbo.sysjobs sj with (nolock)inner join dbo.sysjobHistory sh with (nolock) on sj.job_id = sh.job_id where sj.name = 'My Agent Job'and [sh.Message] like '%The job%') a Now that I had each nightly run time in hours, minutes and seconds (01:10:03), I decided that it would very productive to calculate a rolling run time average. To do this, I decided to do the calculations in base units of seconds. This said, I encapsulated the query shown above into a further ‘super’ query (see the code in RED below). This encapsulation is shown below. The astute reader will note that I used implied casting from integer to string, which is not the best method to use however it works. This said and if I were constructing the query again I would definitely do an explicit convert. To Recap: I now have a key field of ‘1’, each and every applicable run date and the total number of SECONDS that the process ran for each run date, all of this data within the #rawdata1 temporary table. Select 1 as keyy,run_date,(substring(b.run_time,1,2)*3600) + (substring(b.run_time,4,2)*60) + (substring(b.run_time,7,2)) as run_time_in_Seconds,run_time into #rawdata1 from ( select run_date,substring(convert(varchar(20),tt),1,2) + ':' + substring(convert(varchar(20),tt),3,2) + ':' +substring(convert(varchar(20),tt),5,2) as [run_time] from (select sj.name,sh.run_date, sh.run_duration, case when len(sh.run_duration) = 6 then convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 5 then '0' + convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 4 then '00' + convert(varchar(8),sh.run_duration)when len(sh.run_duration)    = 3 then '000' + convert(varchar(8),sh.run_duration)when len(sh.run_duration)    = 2 then '0000' + convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 1 then '00000' + convert(varchar(8),sh.run_duration)end as ttfrom dbo.sysjobs sj with (nolock)inner join dbo.sysjobHistory sh with (nolock)on sj.job_id = sh.job_id where sj.name = 'My Agent Job'and [sh.Message] like '%The job%') a )b   Calculating the average run time We now select each run time in seconds from #rawdata1 and place the values into another temporary table called #rawdata2. Once again we create a ‘key’, a hardwired ‘1’. select 1 as Keyy, run_time_in_Seconds into #rawdata2 from #rawdata1The purpose of doing so is to make the average time AVG() available to the query immediately without having to do adverse grouping. Applying KPI Logic At this point, we shall apply some logic to determine whether processing times are within the norms. We do this by applying colour names. Obviously, this example is a super one for SSRS and traffic light icons.select rd1.run_date, rd1.run_time, rd1.run_time_in_Seconds ,Avg(rd2.run_time_in_Seconds) as Average_run_time_in_seconds,casewhenConvert(decimal(10,1),rd1.run_time_in_Seconds)/Avg(rd2.run_time_in_Seconds)<= 1.2 then 'Green' when Convert(decimal(10,1),rd1.run_time_in_Seconds)/Avg(rd2.run_time_in_Seconds)< 1.4 then 'Yellow' else 'Red'end as [color], Calculating the Average Run Time in Hours Minutes and Seconds and the end of the query. casewhen len(convert(varchar(2),Avg(rd2.run_time_in_Seconds)/(3600))) = 1 then '0' + convert(varchar(2),Avg(rd2.run_time_in_Seconds)/(3600))else convert(varchar(2),Avg(rd2.run_time_in_Seconds)/(3600))end + ':' + case when len(convert(varchar(2),Avg(rd2.run_time_in_Seconds)%(3600)/60)) = 1 then '0' + convert(varchar(2),Avg(rd2.run_time_in_Seconds)%(3600)/60)else convert(varchar(2),Avg(rd2.run_time_in_Seconds)%(3600)/60)end + ':' + case when len(convert(varchar(2),Avg(rd2.run_time_in_Seconds)%60)) = 1 then '0' + convert(varchar(2),Avg(rd2.run_time_in_Seconds)%60)else convert(varchar(2),Avg(rd2.run_time_in_Seconds)%60)end as [Average Run Time HH:MM:SS] from #rawdata2 rd2 innerjoin #rawdata1 rd1on rd1.keyy = rd2.keyygroup by run_date,rd1.run_time ,rd1.run_time_in_Seconds order by run_date descThe complete code example use msdbgo/*drop table #rawdata1drop table #rawdata2go*/select 1 as keyy,run_date,(substring(b.run_time,1,2)*3600) + (substring(b.run_time,4,2)*60) + (substring(b.run_time,7,2)) as run_time_in_Seconds,run_time into #rawdata1 from (select run_date,substring(convert(varchar(20),tt),1,2) + ':' +substring(convert(varchar(20),tt),3,2) + ':' +substring(convert(varchar(20),tt),5,2) as [run_time] from (select name,run_date, run_duration, casewhenlen(run_duration) = 6 then convert(varchar(8),run_duration)whenlen(run_duration) = 5 then '0' + convert(varchar(8),run_duration)whenlen(run_duration) = 4 then '00' + convert(varchar(8),run_duration)whenlen(run_duration) = 3 then '000' + convert(varchar(8),run_duration)whenlen(run_duration) = 2 then '0000' + convert(varchar(8),run_duration)whenlen(run_duration) = 1 then '00000' + convert(varchar(8),run_duration)end as ttfrom dbo.sysjobs sj with (nolock)innerjoin dbo.sysjobHistory sh with (nolock) on sj.job_id = sh.job_id where name = 'My Agent Job'and [Message] like '%The job%') a ) bselect 1 as Keyy, run_time_in_Seconds into #rawdata2 from #rawdata1select rd1.run_date, rd1.run_time, rd1.run_time_in_Seconds ,Avg(rd2.run_time_in_Seconds) as Average_run_time_in_seconds,casewhenConvert(decimal(10,1),rd1.run_time_in_Seconds)/Avg(rd2.run_time_in_Seconds)<= 1.2 then 'Green' when Convert(decimal(10,1),rd1.run_time_in_Seconds)/Avg(rd2.run_time_in_Seconds)< 1.4 then 'Yellow' else 'Red'end as [color],Case when len(convert(varchar(2),Avg(rd2.run_time_in_Seconds)/(3600))) = 1 then '0' + convert(varchar(2),Avg(rd2.run_time_in_Seconds)/(3600))else convert(varchar(2),Avg(rd2.run_time_in_Seconds)/(3600))end + ':' + case when len(convert(varchar(2),Avg(rd2.run_time_in_Seconds)%(3600)/60)) = 1 then '0' + convert(varchar(2),Avg(rd2.run_time_in_Seconds)%(3600)/60)else convert(varchar(2),Avg(rd2.run_time_in_Seconds)%(3600)/60)end + ':' + case when len(convert(varchar(2),Avg(rd2.run_time_in_Seconds)%60)) = 1 then '0' + convert(varchar(2),Avg(rd2.run_time_in_Seconds)%60)else convert(varchar(2),Avg(rd2.run_time_in_Seconds)%60)end as [Average Run Time HH:MM:SS] from #rawdata2 rd2 innerjoin #rawdata1 rd1on rd1.keyy = rd2.keyygroup by run_date,rd1.run_time ,rd1.run_time_in_Seconds order by run_date desc  

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