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  • Cloud Computing Business Benefits

    - by workflowman
    If you have been living under a rock for the past year, you wouldn't have heard about cloud computing. Cloud computing is a loose term that describes anything that is hosted in data centers and accessed via the internet. It is normally associated with developers who draw clouds in diagrams indicating where services or how systems communicate with each other. Cloud computing also incorporates such well-known trends as Web 2.0 and Software as a Service (SaaS) and more recently Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). Its aim is to change the way we compute, moving from traditional desktop and on-premises servers to services and resources that are hosted in the cloud.  Benefits of Cloud Computing  There are clearly benefits in building applications using cloud computing, some of which are listed here:  Zero up- front investment:  Delivering a large-scale system costs a fortune in both time and money. Often IT departments are split into hardware/network and software services. The hardware team provisions servers and so forth under the requirements of the software team. Often the hardware team has a different budget that requires approval. Although hardware and software management are two separate disciplines, sometimes what happens is developers are given the task to estimate CPU cycles, disk space, and so forth, which ends up in underutilized servers.  Usage-based costing:  You pay for what you use, no more, no less, because you never actually own the server. This is similar to car leasing, where in the long run you get a new car every three years and maintenance is never a worry.  Potential for shrinking the processing time:  If processes are split over multiple machines, parallel processing is performed, which decreases processing time.  More office space:  Walk into most offices, and guaranteed you will find a medium- sized room dedicated to servers.  Efficient resource utilization:  The resource utilization is handed by a centralized cloud administrator who is in charge of deciding exactly the right amount of resources for a system. This takes the task away from local administrators, who have to regularly monitor these servers.  Just-in-time infrastructure:  If your system is a success and needs to scale to meet demand, this can cause further time delays or a slow- performing service. Cloud computing solves this because you can add more resources at any time.  Lower environmental impact:  If servers are centralized, potentially an environment initiative is more likely to succeed. As an example, if servers are placed in sunny or windy parts of the world, then why not use these resources to power those servers?  Lower costs:  Unfortunately, this is one point that administrators will not like. If you have people administrating your e-mail server and network along with support staff doing other cloud-based tasks, this workforce can be reduced. This saves costs, though it also reduces jobs.

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  • What is the abstract name for Drive, Directory and file?

    - by Omkar panhalkar
    I want to give nice name to my function while returns drive, directory and file. Can you please suggest a good abstract name for this trio? This is the function. static IEnumerable<string> GetDriveDirectoriesAndFile(string path) { if (path.Contains('/')) { path = path.Replace('/', '\\'); } if (path.Contains('\\')) { return path.Split('\\'); } return null; } Thanks, Omkar

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  • Best way to set up servers for .NET performance [migrated]

    - by msigman
    Assume we have 3 physical servers and let's say we are only interested in performance, and not reliability. Is it better to give each server a specific function or make them all duplicates and split the traffic between them? In other words dedicate 1 as DB server, 1 as web server, and 1 as reporting server/data warehouse, or better to put all three services on each server and use them as web farm?

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  • Why lambdas seem broken in multithreaded environments (or how closures in C# works).

    Ive been playing around with some code for.NET 3.5 to enable us to split big operations into small parallel tasks. During this work I was reminded why Resharper has the Access to modified closure warning. This warning tells us about a inconsistency in handling the Immutable loop variable created in a foreach loop when lambdas [...]...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • How to make my newly created secondary partition accessible?

    - by cipricus
    I have decided to reinstall my Lubuntu OS and to split on the occasion my partition so as to have a secondary one where long-time files would be stored. When trying to install the system onto the smaller one, I was prompted to set a different mount point for the other (different from /). Not knowing what to do I selected /boot for the second and went on installing on the first one. All was ok except that now the larger/secondary (/boot mount point) partition is not visible. In Gparted it is:

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  • Lost partition after restarting

    - by nxhoaf
    I have Window 7 Professional Service pack installed in my Laptop Lenovo Thinkpad t420. After formatting the disk, and install Window 7 (detailed as above), I went to Computer -- Manager -- Storage -- Disk Management to split my 300gb C partition into 2 partition: C (which is 162gb) E (which is 140gb) Is work fine for about 2 days. Today, when I turn on my computer, I'm very suprise that the E partition is disappear. I can surely confirm that I didn't do any stupid thing yesterday. And before I shut down my computer, everything was fine. In general, here is what I did during the last today (from the point that I formatted the disk, and installed Window) Format 300gb hard disk Install window 7 Install eclipse, db2, .... ( I'm a developer) Install some other tools (Open office, Skype...) Install PGP (http://www.symantec.com/encryption) <--- I'm forced to used that due to my company policy Use Computer -- Manager -- Storage -- Disk Management to split my 300gb C partition into 2 partition as described above. It worked quite well for two last days. Until day... Can you please help me to recover my lost partition ? Thank you! For more info, here is my partition info: You can also see the image here

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  • Splitting HDMI sound to 2 devices under Windows 7

    - by Jeramy
    Okay, this is a strange set-up and is frustrating me. I have an HDMI signal from my PC being split to my audio receiver and my HDTV. I need to split it to both so that I can choose to either play audio from the HDTV or from the surround sound speakers in the room. The problem that I am having is in Windows 7, the output is listed under "Playback Devices" and is auto-populated with the HDTV, which only has the option for stereo sound. If I unplug the HDTV from the splitter it will populate with my receiver information and let me set it to 5.1 surround, but as soon as I plug the HDTV back in it reverts. I tried reversing the order of the HDMI cables in the splitter and this seemed to work for a short while, then Windows must have polled the devices again or something because it reverted. It will work as long as Windows identifies the reciever, thereby unlocking the 5.1 surround option, otherwise I am stuck with stereo, which it assumes is all the HDTV is capable of. Is there a way to manually override this and set my own options? Or any other solutions?

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  • emacs, writing custom commands which use term-mode

    - by valya
    Hello, I'm using Emacs and M-x term for a terminal. Since my typical workflow looks like this: edit some code C-x C-o to the terminal buffer (or C-x b term[Enter] or something) press Up key to use the last command press Enter to run it C-x C-o to go back I want to bind all of these (except the first step... maybe) to one command, I believe Emacs is awesome enough to do that :-) So, a command must: go to the buffer with terminal (maybe it shouldn't change any windows at all, maybe it should split the window vertially (if it weren't split already) and use the right sid) run a last command what've been run there go back to the last buffer/part of the screen Thank you! I'm not really used to the Emacs scripting system, and I hope someone will help me and someone else will be able to use the answer to improve his workflow, since I believe this is a pretty common one Examples of commands: python manage.py test python manage.py test stats python solve.py # for project-euler puzzles :-) the first and the second runs over a ssh (in a terminal) sometimes (I like developing with vagrant) I understand that it's easy to bind the first and the third ones, but the second changes too often - I'd just like to "run last command"

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  • Downmix ALL SYSTEM audio to mono - Windows 7

    - by Mike K.
    I'm deaf in one ear and want to use my headphones when playing a game and talking with my friends on Skype/TS/Mumble/etc while also sometimes listening to music. I need ALL my system audio to be downmixed to mono so that my ONE hearing ear gets ALL audio channels instead of split stereo audio. No, none of the other similar questions on superuser have a solution. My headphone properties does not have a 'Mono' option, I don't have a 'Headphone Virtualization' option, and my Realtek HD audio driver software doesn't have these options either (driver was updated 11/14/2012). Don't even talk about setting the balance of one side of the headphones to 0. You're not paying attention if you suggest that. JACK and Virtual Audio Cable didn't work. It's possible I configured them wrong, but I followed the steps I found in related questions and still got split stereo out. TL;DR I need a viable, working, software solution (I say software because I have a USB headset) for forcing ALL system audio to mono so that I can hear literally everything through the one earpiece. Thanks!

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  • Linux Scheduler (not using all cores on multi-core machine) RHEL6

    - by User512
    I'm seeing strange behavior on one of my servers (running RHEL 6). There seems to be something wrong with the scheduler. Here's the test program I'm using: #include <stdio.h> #include <unistd.h> #include <stdlib.h> void RunClient(int i) { printf("Starting client %d\n", i); while (true) { } } int main(int argc, char** argv) { for (int i = 0; i < 4; ++i) { pid_t p_id = fork(); if (p_id == -1) { perror("fork"); } else if (p_id == 0) { RunClient(i); exit(0); } } return 0; } This machine has a lot more than 4 cores so we'd expect all processes to be running at 100%. When I check on top, the cpu usage varies. Sometimes it's split (100%, 33%, 33%, 33%), other times it's split (100%, 100%, 50%, 50%). When I try this test on another server of ours (running RHEL 5), there are no issues (it's 100%, 100%, 100%, 100%) as expected. What's causing this and how can I fix it? Thanks

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  • Files on ext4 on Drobo with corrupt, zero-ed out blocks

    - by Patrick
    I have a 2TB ext4 file system (Ubuntu running Linux kernel 2.6.31-22-server x86_64). This file system is the second drive on a Drobo box plugged in via USB. We've not had problems on the first drive (Drobo limits drive size to 2TB due to some OS limitations, so if you have more space than that it appears as two separate drives). I am sharing this files with Samba (smbd 3.4.0) with a mix of Windows and Linux workstations. Recently we've been experiencing some data corruption in multiple files. In many cases I have an un-corrupt original file stored on one of the workstations. These are binary files of various formats, (e.g. SQLite, but others as well). I used "split" to split a corrupt and uncorrupt file into 4096 byte chunks (this is the block size of the ext4 file system). I then ran md5sum on pairs of chunks and discovered that the chunks matched in many cases and in every case where they did not match, the corrupt chunk was a solid chunk of zeroes (620f0b67a91f7f74151bc5be745b7110 for what it's worth). I'm trying to track down a culprit but am a bit at a loss. I don't believe Samba is at fault since I'm using it without issue on the first drive exported by the Drobo. What can I do to narrow this down and find out what's going on?

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  • Skip Corrupt Revisions During SvnAdmin Load

    - by cisellis
    I have a dump file that I am generating from VSS with the use of the VSS2SVN script. I've tested the generated dump file before and some of the revisions are corrupt for one reason or another (binary data or long path strings seem to be the main culprit). This is fine. In the past I have used svndumpfilter to split the dump file, remove the corrupt revisions and continue to load the repository. It worked but took a lot of manual effort to start the load, hit the bad revision, split the dump file, continue loading the repo, etc. This dump file is pretty large (~5GB) and takes several hours to load. I think I know the answer to this but is there any way to simply tell svnadmin load to keep going and skip corrupt revisions? I know how to verify, backup, etc. the dump file and don't need any of that. I don't care about recovering corrupt revisions. I just want to start the load, walk away, and not worry about checking it every few hours to manually remove the corrupt revisions. Is that possible? Thanks.

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  • Distributing processing for an application that wasn't designed with that in mind

    - by Tim
    We've got the application at work that just sits and does a whole bunch of iterative processing on some data files to perform some simulations. This is done by an "old" Win32 application that isn't multi-processor aware, so new(ish) computers and workstations are mostly sitting idle running this application. However, since it's installed by a typical Windows Install Shield installer, I can't seem to install and run multiple copies of the application. The work can be split up manually before processing, enabling the work to be distributed across multiple machines, but we still can't take advantage of multiple core CPUs. The results can be joined back together after processing to make a complete simulation. Is there a product out there that would let me "compartmentalize" an installation (or 4) so I can take advantage of a multi-core CPU? I had thought of using MS Softgrid, but I believe that still depends on a remote server to do the heavy lifting (though please correct me if I'm wrong). Furthermore, is there a way I can distribute the workload off the one machine? So an input could be split into 50 chunks, handed out to 50 machines, and worked on? All without really changing the initial application? In a perfect world, I'd get the application to take advantage of a DesktopGrid (BOINC), but like most "mission critical corporate applications", the need is there, but the money is not. Thank you in advance (and sorry if this isn't appropriate for serverfault).

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  • gitolite mac don't add new user to authorized_keys

    - by crashbus
    I installed gitolite and every thing works fine for me as admin. But when I'd like to add add a new user the new user can't connect to the server. After I looked into the file authorized_keys I saw that the new user wasn't added to the file. During the commit of the new public-key I get some workings: WARNING: split conf not set, gl-conf present for 'gitolite-admin' Counting objects: 6, done. Delta compression using up to 8 threads. Compressing objects: 100% (4/4), done. Writing objects: 100% (4/4), 882 bytes, done. Total 4 (delta 1), reused 0 (delta 0) remote: WARNING: split conf not set, gl-conf present for 'gitolite-admin' remote: WARNING: ?? @staff christianwaldmann markwelch remote: sh: find: command not found remote: sh: find: command not found remote: sh: sort: command not found remote: sh: find: command not found remote: /usr/local/bin/triggers/post-compile/update-gitweb-access-list: line 26: cut: command not found remote: /usr/local/bin/triggers/post-compile/update-gitweb-access-list: line 23: grep: command not found remote: /usr/local/bin/triggers/post-compile/update-gitweb-access-list: line 26: sort: command not found remote: /usr/local/bin/triggers/post-compile/update-gitweb-access-list: line 26: sed: command not found remote: sh: find: command not found remote: sh: find: command not found How can I fix it that gitolite auto-add the new user to the authorized_keys.

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  • iSCSI performance questions

    - by RyanLambert
    Hi everyone, apologies for the long-winded post in advance... Attempting to troubleshoot some iSCSI sluggishness on a brand new vSphere deployment (still in test). Layout is as such: 3 VSphere hosts, each with 2x 10GB NICs plugged into a pair of Nexus 5020s with a 10gig back-to-back between them. NICs are port-channeled in an active/active redundant fashion (using vPC-mac pinning for those of you familiar with N1KV) Both NICs carry service console, vmotion, iSCSI, and guest traffic. iSCSI is on a single subnet/single VLAN that is not routed through our IP network (strictly layer2) Had this been a 1gig deployment, we probably would have split the iSCSI traffic off onto separate NICs, but the price/port gets rather ridiculous when you start throwing 4+ NICs to a server in a 10gigabit infrastructure, and I'm not really convinced it's necessary. Open to dialogue/tech facts re: this, though. At this point even a single VM guest will boot slowly to iSCSI storage (EMC CX4 on the same Nexus 5020 10gig switches), and restores of VMs from iSCSI take about twice as long as we'd expect them to. Our server folks mentioned that if we split the iSCSI off onto its own NIC, performance seems significantly better. From a network perspective, I've run through the variables I can think of (port configuration errors, MTU problems, congestion etc.) and I'm coming up dry. There really is no other traffic on these hosts other than the very specific test being performed at the time. Important thing to note is that guest traffic works just fine... it seems storage is the only thing affected by whatever gremlin exists. Concluding that we're not 'overutilizing' the network infrastructure since we're doing hardly anything, I'm just looking for some helpful tips/ideas we can use to resolve this... preferably without hurling extra 10gig NICs that are going to sit around 10% utilization while we've got 70+% left on our others.

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  • Logging won't stop on log file after renaming/moving it.... how do I stop it?

    - by Jakobud
    Just discovered that logrotate is not rotating our firewall log. So its up to 12g in size. I need to split up the file into smaller chunks and start manually rotating them so I can get things back on track. However before I start splitting the firewall up, I need to stop the firewall from logging to the current firewall log file and force it to start logging to a new empty file. This way I'm not trying to split up or rotate a log file that is still constantly growing. I tried to simply do this: mv firewall firewall.old touch firewall I expected to see the new empty firewall file to start growing in size, but no... the firewall.old is still be logged to. Then I tried to start/stop iptables. No change. firewall.old is still the log file. I tried to move it to another directory. That didn't help. I tried to stop iptables, then change the filename and create a new firewall file and then start iptables again, but no change. How do I stop the logging on this file and force it to start logging on a new file?

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  • Motherboard Dying? AHCI Drive Init and boot loop intermittent failure

    - by Adam Heath
    My computer is now intermittently failing to boot up. For the last couple of days, when I turn it on it hangs on "AHCI Drive Init...", and when powered off and on again, it booted up fine. Today, it did the same but failed in a few other ways too, seemingly at random: Hangs on "AHCI Drive Init..." Boot loop (after "AHCI Drive Init..." appears for a split second (no drives listed)) Black screen (after "AHCI Drive Init..." appears for a split second, a black screen with all fans still running) The interesting part is that the above is not affected by what drives are connected, or what to. I have tried both disks, each disk individually and no disks (along with trying the primary and secondary SATA controllers), none of this has any effect on what happens. After about 20+ attempts of different combinations, it suddenly decided it would boot up into Windows, and I hadn't touched anything for about 2 cycles. Motherboard: Gigabyte GA-870A-USB3 Processor: Amd Phoenom II x6 1090T RAM: 8GB Corsair 1600 Primary Disk: Plextor 128GB SSD Secondary Disk: Western Digital Black 1TB OS: Windows 8.1 Is this my motherboard dying? Or could something else be the cause? Thanks!

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  • Computer wont start, just blinks on and off

    - by Ryan
    This is really strange. I had a comp that was working fine for over a year, then suddenly it started to shut off, it got so bad that I press the power button and in around 30 secs while booting windows it would shut off, then 20 secs... then 10 secs, then it refused to start all together. So I bought a new PSU (850w Thermaltake, the old one was 550w corsair) thinking that was the problem, I fitted the new PSU now and its the same thing, I press the power button and my fans start for a split second (they have led lights on them, so the lights come on) and then everything goes off again. I thought maybe it was my power button that was loose on my comp, luckily I had another chassis near by so I disconnected the powerSW from the old one and put ran the powerSW from the new chassis, press the power on the new chassis and same thing, it blinks for a split second and off again. Double checked connections from the PSU to the cpu power as well as board mobo power, its tight. It's pretty unlikely both the PSUs have the same exact problem so am lost... Suggestions?

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  • Logging won't stop on log file after renaming/moving it.... how do I stop it?

    - by Jakobud
    Just discovered that logrotate is not rotating our firewall log. So it's up to 12G in size. I need to split up the file into smaller chunks and start manually rotating them so I can get things back on track. However before I start splitting the firewall up, I need to stop the firewall from logging to the current firewall log file and force it to start logging to a new empty file. This way I'm not trying to split up or rotate a log file that is still constantly growing. I tried to simply do this: mv firewall firewall.old touch firewall I expected to see the new empty firewall file to start growing in size, but no... the firewall.old is still be logged to. Then I tried to start/stop iptables. No change. firewall.old is still the log file. I tried to move it to another directory. That didn't help. I tried to stop iptables, then change the filename and create a new firewall file and then start iptables again, but no change. How do I stop the logging on this file and force it to start logging on a new file?

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  • Where can these be posted besides the Python Cookbook?

    - by Noctis Skytower
    Whitespace Assembler #! /usr/bin/env python """Assembler.py Compiles a program from "Assembly" folder into "Program" folder. Can be executed directly by double-click or on the command line. Give name of *.WSA file without extension (example: stack_calc).""" ################################################################################ __author__ = 'Stephen "Zero" Chappell <[email protected]>' __date__ = '14 March 2010' __version__ = '$Revision: 3 $' ################################################################################ import string from Interpreter import INS, MNEMONIC ################################################################################ def parse(code): program = [] process_virtual(program, code) process_control(program) return tuple(program) def process_virtual(program, code): for line, text in enumerate(code.split('\n')): if not text or text[0] == '#': continue if text.startswith('part '): parse_part(program, line, text[5:]) elif text.startswith(' '): parse_code(program, line, text[5:]) else: syntax_error(line) def syntax_error(line): raise SyntaxError('Line ' + str(line + 1)) ################################################################################ def process_control(program): parts = get_parts(program) names = dict(pair for pair in zip(parts, generate_index())) correct_control(program, names) def get_parts(program): parts = [] for ins in program: if isinstance(ins, tuple): ins, arg = ins if ins == INS.PART: if arg in parts: raise NameError('Part definition was found twice: ' + arg) parts.append(arg) return parts def generate_index(): index = 1 while True: yield index index *= -1 if index > 0: index += 1 def correct_control(program, names): for index, ins in enumerate(program): if isinstance(ins, tuple): ins, arg = ins if ins in HAS_LABEL: if arg not in names: raise NameError('Part definition was never found: ' + arg) program[index] = (ins, names[arg]) ################################################################################ def parse_part(program, line, text): if not valid_label(text): syntax_error(line) program.append((INS.PART, text)) def valid_label(text): if not between_quotes(text): return False label = text[1:-1] if not valid_name(label): return False return True def between_quotes(text): if len(text) < 3: return False if text.count('"') != 2: return False if text[0] != '"' or text[-1] != '"': return False return True def valid_name(label): valid_characters = string.ascii_letters + string.digits + '_' valid_set = frozenset(valid_characters) label_set = frozenset(label) if len(label_set - valid_set) != 0: return False return True ################################################################################ from Interpreter import HAS_LABEL, Program NO_ARGS = Program.NO_ARGS HAS_ARG = Program.HAS_ARG TWO_WAY = tuple(set(NO_ARGS) & set(HAS_ARG)) ################################################################################ def parse_code(program, line, text): for ins, word in enumerate(MNEMONIC): if text.startswith(word): check_code(program, line, text[len(word):], ins) break else: syntax_error(line) def check_code(program, line, text, ins): if ins in TWO_WAY: if text: number = parse_number(line, text) program.append((ins, number)) else: program.append(ins) elif ins in HAS_LABEL: text = parse_label(line, text) program.append((ins, text)) elif ins in HAS_ARG: number = parse_number(line, text) program.append((ins, number)) elif ins in NO_ARGS: if text: syntax_error(line) program.append(ins) else: syntax_error(line) def parse_label(line, text): if not text or text[0] != ' ': syntax_error(line) text = text[1:] if not valid_label(text): syntax_error(line) return text ################################################################################ def parse_number(line, text): if not valid_number(text): syntax_error(line) return int(text) def valid_number(text): if len(text) < 2: return False if text[0] != ' ': return False text = text[1:] if '+' in text and '-' in text: return False if '+' in text: if text.count('+') != 1: return False if text[0] != '+': return False text = text[1:] if not text: return False if '-' in text: if text.count('-') != 1: return False if text[0] != '-': return False text = text[1:] if not text: return False valid_set = frozenset(string.digits) value_set = frozenset(text) if len(value_set - valid_set) != 0: return False return True ################################################################################ ################################################################################ from Interpreter import partition_number VMC_2_TRI = { (INS.PUSH, True): (0, 0), (INS.COPY, False): (0, 2, 0), (INS.COPY, True): (0, 1, 0), (INS.SWAP, False): (0, 2, 1), (INS.AWAY, False): (0, 2, 2), (INS.AWAY, True): (0, 1, 2), (INS.ADD, False): (1, 0, 0, 0), (INS.SUB, False): (1, 0, 0, 1), (INS.MUL, False): (1, 0, 0, 2), (INS.DIV, False): (1, 0, 1, 0), (INS.MOD, False): (1, 0, 1, 1), (INS.SET, False): (1, 1, 0), (INS.GET, False): (1, 1, 1), (INS.PART, True): (2, 0, 0), (INS.CALL, True): (2, 0, 1), (INS.GOTO, True): (2, 0, 2), (INS.ZERO, True): (2, 1, 0), (INS.LESS, True): (2, 1, 1), (INS.BACK, False): (2, 1, 2), (INS.EXIT, False): (2, 2, 2), (INS.OCHR, False): (1, 2, 0, 0), (INS.OINT, False): (1, 2, 0, 1), (INS.ICHR, False): (1, 2, 1, 0), (INS.IINT, False): (1, 2, 1, 1) } ################################################################################ def to_trinary(program): trinary_code = [] for ins in program: if isinstance(ins, tuple): ins, arg = ins trinary_code.extend(VMC_2_TRI[(ins, True)]) trinary_code.extend(from_number(arg)) else: trinary_code.extend(VMC_2_TRI[(ins, False)]) return tuple(trinary_code) def from_number(arg): code = [int(arg < 0)] if arg: for bit in reversed(list(partition_number(abs(arg), 2))): code.append(bit) return code + [2] return code + [0, 2] to_ws = lambda trinary: ''.join(' \t\n'[index] for index in trinary) def compile_wsa(source): program = parse(source) trinary = to_trinary(program) ws_code = to_ws(trinary) return ws_code ################################################################################ ################################################################################ import os import sys import time import traceback def main(): name, source, command_line, error = get_source() if not error: start = time.clock() try: ws_code = compile_wsa(source) except: print('ERROR: File could not be compiled.\n') traceback.print_exc() error = True else: path = os.path.join('Programs', name + '.ws') try: open(path, 'w').write(ws_code) except IOError as err: print(err) error = True else: div, mod = divmod((time.clock() - start) * 1000, 1) args = int(div), '{:.3}'.format(mod)[1:] print('DONE: Comipled in {}{} ms'.format(*args)) handle_close(error, command_line) def get_source(): if len(sys.argv) > 1: command_line = True name = sys.argv[1] else: command_line = False try: name = input('Source File: ') except: return None, None, False, True print() path = os.path.join('Assembly', name + '.wsa') try: return name, open(path).read(), command_line, False except IOError as err: print(err) return None, None, command_line, True def handle_close(error, command_line): if error: usage = 'Usage: {} <assembly>'.format(os.path.basename(sys.argv[0])) print('\n{}\n{}'.format('-' * len(usage), usage)) if not command_line: time.sleep(10) ################################################################################ if __name__ == '__main__': main() Whitespace Helpers #! /usr/bin/env python """Helpers.py Includes a function to encode Python strings into my WSA format. Has a "PRINT_LINE" function that can be copied to a WSA program. Contains a "PRINT" function and documentation as an explanation.""" ################################################################################ __author__ = 'Stephen "Zero" Chappell <[email protected]>' __date__ = '14 March 2010' __version__ = '$Revision: 1 $' ################################################################################ def encode_string(string, addr): print(' push', addr) print(' push', len(string)) print(' set') addr += 1 for offset, character in enumerate(string): print(' push', addr + offset) print(' push', ord(character)) print(' set') ################################################################################ # Prints a string with newline. # push addr # call "PRINT_LINE" """ part "PRINT_LINE" call "PRINT" push 10 ochr back """ ################################################################################ # def print(array): # if len(array) <= 0: # return # offset = 1 # while len(array) - offset >= 0: # ptr = array.ptr + offset # putch(array[ptr]) # offset += 1 """ part "PRINT" # Line 1-2 copy get less "__PRINT_RET_1" copy get zero "__PRINT_RET_1" # Line 3 push 1 # Line 4 part "__PRINT_LOOP" copy copy 2 get swap sub less "__PRINT_RET_2" # Line 5 copy 1 copy 1 add # Line 6 get ochr # Line 7 push 1 add goto "__PRINT_LOOP" part "__PRINT_RET_2" away part "__PRINT_RET_1" away back """ Whitespace Interpreter #! /usr/bin/env python """Interpreter.py Runs programs in "Programs" and creates *.WSO files when needed. Can be executed directly by double-click or on the command line. If run on command line, add "ASM" flag to dump program assembly.""" ################################################################################ __author__ = 'Stephen "Zero" Chappell <[email protected]>' __date__ = '14 March 2010' __version__ = '$Revision: 4 $' ################################################################################ def test_file(path): disassemble(parse(trinary(load(path))), True) ################################################################################ load = lambda ws: ''.join(c for r in open(ws) for c in r if c in ' \t\n') trinary = lambda ws: tuple(' \t\n'.index(c) for c in ws) ################################################################################ def enum(names): names = names.replace(',', ' ').split() space = dict((reversed(pair) for pair in enumerate(names)), __slots__=()) return type('enum', (object,), space)() INS = enum('''\ PUSH, COPY, SWAP, AWAY, \ ADD, SUB, MUL, DIV, MOD, \ SET, GET, \ PART, CALL, GOTO, ZERO, LESS, BACK, EXIT, \ OCHR, OINT, ICHR, IINT''') ################################################################################ def parse(code): ins = iter(code).__next__ program = [] while True: try: imp = ins() except StopIteration: return tuple(program) if imp == 0: # [Space] parse_stack(ins, program) elif imp == 1: # [Tab] imp = ins() if imp == 0: # [Tab][Space] parse_math(ins, program) elif imp == 1: # [Tab][Tab] parse_heap(ins, program) else: # [Tab][Line] parse_io(ins, program) else: # [Line] parse_flow(ins, program) def parse_number(ins): sign = ins() if sign == 2: raise StopIteration() buffer = '' code = ins() if code == 2: raise StopIteration() while code != 2: buffer += str(code) code = ins() if sign == 1: return int(buffer, 2) * -1 return int(buffer, 2) ################################################################################ def parse_stack(ins, program): code = ins() if code == 0: # [Space] number = parse_number(ins) program.append((INS.PUSH, number)) elif code == 1: # [Tab] code = ins() number = parse_number(ins) if code == 0: # [Tab][Space] program.append((INS.COPY, number)) elif code == 1: # [Tab][Tab] raise StopIteration() else: # [Tab][Line] program.append((INS.AWAY, number)) else: # [Line] code = ins() if code == 0: # [Line][Space] program.append(INS.COPY) elif code == 1: # [Line][Tab] program.append(INS.SWAP) else: # [Line][Line] program.append(INS.AWAY) def parse_math(ins, program): code = ins() if code == 0: # [Space] code = ins() if code == 0: # [Space][Space] program.append(INS.ADD) elif code == 1: # [Space][Tab] program.append(INS.SUB) else: # [Space][Line] program.append(INS.MUL) elif code == 1: # [Tab] code = ins() if code == 0: # [Tab][Space] program.append(INS.DIV) elif code == 1: # [Tab][Tab] program.append(INS.MOD) else: # [Tab][Line] raise StopIteration() else: # [Line] raise StopIteration() def parse_heap(ins, program): code = ins() if code == 0: # [Space] program.append(INS.SET) elif code == 1: # [Tab] program.append(INS.GET) else: # [Line] raise StopIteration() def parse_io(ins, program): code = ins() if code == 0: # [Space] code = ins() if code == 0: # [Space][Space] program.append(INS.OCHR) elif code == 1: # [Space][Tab] program.append(INS.OINT) else: # [Space][Line] raise StopIteration() elif code == 1: # [Tab] code = ins() if code == 0: # [Tab][Space] program.append(INS.ICHR) elif code == 1: # [Tab][Tab] program.append(INS.IINT) else: # [Tab][Line] raise StopIteration() else: # [Line] raise StopIteration() def parse_flow(ins, program): code = ins() if code == 0: # [Space] code = ins() label = parse_number(ins) if code == 0: # [Space][Space] program.append((INS.PART, label)) elif code == 1: # [Space][Tab] program.append((INS.CALL, label)) else: # [Space][Line] program.append((INS.GOTO, label)) elif code == 1: # [Tab] code = ins() if code == 0: # [Tab][Space] label = parse_number(ins) program.append((INS.ZERO, label)) elif code == 1: # [Tab][Tab] label = parse_number(ins) program.append((INS.LESS, label)) else: # [Tab][Line] program.append(INS.BACK) else: # [Line] code = ins() if code == 2: # [Line][Line] program.append(INS.EXIT) else: # [Line][Space] or [Line][Tab] raise StopIteration() ################################################################################ MNEMONIC = '\ push copy swap away add sub mul div mod set get part \ call goto zero less back exit ochr oint ichr iint'.split() HAS_ARG = [getattr(INS, name) for name in 'PUSH COPY AWAY PART CALL GOTO ZERO LESS'.split()] HAS_LABEL = [getattr(INS, name) for name in 'PART CALL GOTO ZERO LESS'.split()] def disassemble(program, names=False): if names: names = create_names(program) for ins in program: if isinstance(ins, tuple): ins, arg = ins assert ins in HAS_ARG has_arg = True else: assert INS.PUSH <= ins <= INS.IINT has_arg = False if ins == INS.PART: if names: print(MNEMONIC[ins], '"' + names[arg] + '"') else: print(MNEMONIC[ins], arg) elif has_arg and ins in HAS_ARG: if ins in HAS_LABEL and names: assert arg in names print(' ' + MNEMONIC[ins], '"' + names[arg] + '"') else: print(' ' + MNEMONIC[ins], arg) else: print(' ' + MNEMONIC[ins]) ################################################################################ def create_names(program): names = {} number = 1 for ins in program: if isinstance(ins, tuple) and ins[0] == INS.PART: label = ins[1] assert label not in names names[label] = number_to_name(number) number += 1 return names def number_to_name(number): name = '' for offset in reversed(list(partition_number(number, 27))): if offset: name += chr(ord('A') + offset - 1) else: name += '_' return name def partition_number(number, base): div, mod = divmod(number, base) yield mod while div: div, mod = divmod(div, base) yield mod ################################################################################ CODE = (' \t\n', ' \n ', ' \t \t\n', ' \n\t', ' \n\n', ' \t\n \t\n', '\t ', '\t \t', '\t \n', '\t \t ', '\t \t\t', '\t\t ', '\t\t\t', '\n \t\n', '\n \t \t\n', '\n \n \t\n', '\n\t \t\n', '\n\t\t \t\n', '\n\t\n', '\n\n\n', '\t\n ', '\t\n \t', '\t\n\t ', '\t\n\t\t') EXAMPLE = ''.join(CODE) ################################################################################ NOTES = '''\ STACK ===== push number copy copy number swap away away number MATH ==== add sub mul div mod HEAP ==== set get FLOW ==== part label call label goto label zero label less label back exit I/O === ochr oint ichr iint''' ################################################################################ ################################################################################ class Stack: def __init__(self): self.__data = [] # Stack Operators def push(self, number): self.__data.append(number) def copy(self, number=None): if number is None: self.__data.append(self.__data[-1]) else: size = len(self.__data) index = size - number - 1 assert 0 <= index < size self.__data.append(self.__data[index]) def swap(self): self.__data[-2], self.__data[-1] = self.__data[-1], self.__data[-2] def away(self, number=None): if number is None: self.__data.pop() else: size = len(self.__data) index = size - number - 1 assert 0 <= index < size del self.__data[index:-1] # Math Operators def add(self): suffix = self.__data.pop() prefix = self.__data.pop() self.__data.append(prefix + suffix) def sub(self): suffix = self.__data.pop() prefix = self.__data.pop() self.__data.append(prefix - suffix) def mul(self): suffix = self.__data.pop() prefix = self.__data.pop() self.__data.append(prefix * suffix) def div(self): suffix = self.__data.pop() prefix = self.__data.pop() self.__data.append(prefix // suffix) def mod(self): suffix = self.__data.pop() prefix = self.__data.pop() self.__data.append(prefix % suffix) # Program Operator def pop(self): return self.__data.pop() ################################################################################ class Heap: def __init__(self): self.__data = {} def set_(self, addr, item): if item: self.__data[addr] = item elif addr in self.__data: del self.__data[addr] def get_(self, addr): return self.__data.get(addr, 0) ################################################################################ import os import zlib import msvcrt import pickle import string class CleanExit(Exception): pass NOP = lambda arg: None DEBUG_WHITESPACE = False ################################################################################ class Program: NO_ARGS = INS.COPY, INS.SWAP, INS.AWAY, INS.ADD, \ INS.SUB, INS.MUL, INS.DIV, INS.MOD, \ INS.SET, INS.GET, INS.BACK, INS.EXIT, \ INS.OCHR, INS.OINT, INS.ICHR, INS.IINT HAS_ARG = INS.PUSH, INS.COPY, INS.AWAY, INS.PART, \ INS.CALL, INS.GOTO, INS.ZERO, INS.LESS def __init__(self, code): self.__data = code self.__validate() self.__build_jump() self.__check_jump() self.__setup_exec() def __setup_exec(self): self.__iptr = 0 self.__stck = stack = Stack() self.__heap = Heap() self.__cast = [] self.__meth = (stack.push, stack.copy, stack.swap, stack.away, stack.add, stack.sub, stack.mul, stack.div, stack.mod, self.__set, self.__get, NOP, self.__call, self.__goto, self.__zero, self.__less, self.__back, self.__exit, self.__ochr, self.__oint, self.__ichr, self.__iint) def step(self): ins = self.__data[self.__iptr] self.__iptr += 1 if isinstance(ins, tuple): self.__meth[ins[0]](ins[1]) else: self.__meth[ins]() def run(self): while True: ins = self.__data[self.__iptr] self.__iptr += 1 if isinstance(ins, tuple): self.__meth[ins[0]](ins[1]) else: self.__meth[ins]() def __oint(self): for digit in str(self.__stck.pop()): msvcrt.putwch(digit) def __ichr(self): addr = self.__stck.pop() # Input Routine while msvcrt.kbhit(): msvcrt.getwch() while True: char = msvcrt.getwch() if char in '\x00\xE0': msvcrt.getwch() elif char in string.printable: char = char.replace('\r', '\n') msvcrt.putwch(char) break item = ord(char) # Storing Number self.__heap.set_(addr, item) def __iint(self): addr = self.__stck.pop() # Input Routine while msvcrt.kbhit(): msvcrt.getwch() buff = '' char = msvcrt.getwch() while char != '\r' or not buff: if char in '\x00\xE0': msvcrt.getwch() elif char in '+-' and not buff: msvcrt.putwch(char) buff += char elif '0' <= char <= '9': msvcrt.putwch(char) buff += char elif char == '\b': if buff: buff = buff[:-1] msvcrt.putwch(char) msvcrt.putwch(' ') msvcrt.putwch(char) char = msvcrt.getwch() msvcrt.putwch(char) msvcrt.putwch('\n') item = int(buff) # Storing Number self.__heap.set_(addr, item) def __goto(self, label): self.__iptr = self.__jump[label] def __zero(self, label): if self.__stck.pop() == 0: self.__iptr = self.__jump[label] def __less(self, label): if self.__stck.pop() < 0: self.__iptr = self.__jump[label] def __exit(self): self.__setup_exec() raise CleanExit() def __set(self): item = self.__stck.pop() addr = self.__stck.po

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  • ORDER BY job failed in the Pig script while running EmbeddedPig using Java

    - by C.c. Huang
    I have this following pig script, which works perfectly using grunt shell (stored the results to HDFS without any issues); however, the last job (ORDER BY) failed if I ran the same script using Java EmbeddedPig. If I replace the ORDER BY job by others, such as GROUP or FOREACH GENERATE, the whole script then succeeded in Java EmbeddedPig. So I think it's the ORDER BY which causes the issue. Anyone has any experience with this? Any help would be appreciated! The Pig script: REGISTER pig-udf-0.0.1-SNAPSHOT.jar; user_similarity = LOAD '/tmp/sample-sim-score-results-31/part-r-00000' USING PigStorage('\t') AS (user_id: chararray, sim_user_id: chararray, basic_sim_score: float, alt_sim_score: float); simplified_user_similarity = FOREACH user_similarity GENERATE $0 AS user_id, $1 AS sim_user_id, $2 AS sim_score; grouped_user_similarity = GROUP simplified_user_similarity BY user_id; ordered_user_similarity = FOREACH grouped_user_similarity { sorted = ORDER simplified_user_similarity BY sim_score DESC; top = LIMIT sorted 10; GENERATE group, top; }; top_influencers = FOREACH ordered_user_similarity GENERATE com.aol.grapevine.similarity.pig.udf.AssignPointsToTopInfluencer($1, 10); all_influence_scores = FOREACH top_influencers GENERATE FLATTEN($0); grouped_influence_scores = GROUP all_influence_scores BY bag_of_topSimUserTuples::user_id; influence_scores = FOREACH grouped_influence_scores GENERATE group AS user_id, SUM(all_influence_scores.bag_of_topSimUserTuples::points) AS influence_score; ordered_influence_scores = ORDER influence_scores BY influence_score DESC; STORE ordered_influence_scores INTO '/tmp/cc-test-results-1' USING PigStorage(); The error log from Pig: 12/04/05 10:00:56 INFO pigstats.ScriptState: Pig script settings are added to the job 12/04/05 10:00:56 INFO mapReduceLayer.JobControlCompiler: mapred.job.reduce.markreset.buffer.percent is not set, set to default 0.3 12/04/05 10:00:58 INFO mapReduceLayer.JobControlCompiler: Setting up single store job 12/04/05 10:00:58 INFO jvm.JvmMetrics: Cannot initialize JVM Metrics with processName=JobTracker, sessionId= - already initialized 12/04/05 10:00:58 INFO mapReduceLayer.MapReduceLauncher: 1 map-reduce job(s) waiting for submission. 12/04/05 10:00:58 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same. 12/04/05 10:00:58 INFO input.FileInputFormat: Total input paths to process : 1 12/04/05 10:00:58 INFO util.MapRedUtil: Total input paths to process : 1 12/04/05 10:00:58 INFO util.MapRedUtil: Total input paths (combined) to process : 1 12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Creating tmp-1546565755 in /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134-work-6955502337234509704 with rwxr-xr-x 12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Cached hdfs://localhost/tmp/temp1725960134/tmp-1546565755#pigsample_854728855_1333645258470 as /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134/tmp-1546565755 12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Cached hdfs://localhost/tmp/temp1725960134/tmp-1546565755#pigsample_854728855_1333645258470 as /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134/tmp-1546565755 12/04/05 10:00:58 WARN mapred.LocalJobRunner: LocalJobRunner does not support symlinking into current working dir. 12/04/05 10:00:58 INFO mapred.TaskRunner: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134/tmp-1546565755 <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/pigsample_854728855_1333645258470 12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/.job.jar.crc <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/.job.jar.crc 12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/.job.split.crc <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/.job.split.crc 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/.job.splitmetainfo.crc <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/.job.splitmetainfo.crc 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/.job.xml.crc <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/.job.xml.crc 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/job.jar <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/job.jar 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/job.split <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/job.split 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/job.splitmetainfo <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/job.splitmetainfo 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/job.xml <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/job.xml 12/04/05 10:00:59 INFO mapred.Task: Using ResourceCalculatorPlugin : null 12/04/05 10:00:59 INFO mapred.MapTask: io.sort.mb = 100 12/04/05 10:00:59 INFO mapred.MapTask: data buffer = 79691776/99614720 12/04/05 10:00:59 INFO mapred.MapTask: record buffer = 262144/327680 12/04/05 10:00:59 WARN mapred.LocalJobRunner: job_local_0004 java.lang.RuntimeException: org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not exist: file:/Users/cchuang/workspace/grapevine-rec/pigsample_854728855_1333645258470 at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.partitioners.WeightedRangePartitioner.setConf(WeightedRangePartitioner.java:139) at org.apache.hadoop.util.ReflectionUtils.setConf(ReflectionUtils.java:62) at org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:117) at org.apache.hadoop.mapred.MapTask$NewOutputCollector.<init>(MapTask.java:560) at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:639) at org.apache.hadoop.mapred.MapTask.run(MapTask.java:323) at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:210) Caused by: org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not exist: file:/Users/cchuang/workspace/grapevine-rec/pigsample_854728855_1333645258470 at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.listStatus(FileInputFormat.java:231) at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigFileInputFormat.listStatus(PigFileInputFormat.java:37) at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.getSplits(FileInputFormat.java:248) at org.apache.pig.impl.io.ReadToEndLoader.init(ReadToEndLoader.java:153) at org.apache.pig.impl.io.ReadToEndLoader.<init>(ReadToEndLoader.java:115) at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.partitioners.WeightedRangePartitioner.setConf(WeightedRangePartitioner.java:112) ... 6 more 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Deleted path /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134/tmp-1546565755 12/04/05 10:00:59 INFO mapReduceLayer.MapReduceLauncher: HadoopJobId: job_local_0004 12/04/05 10:01:04 INFO mapReduceLayer.MapReduceLauncher: job job_local_0004 has failed! Stop running all dependent jobs 12/04/05 10:01:04 INFO mapReduceLayer.MapReduceLauncher: 100% complete 12/04/05 10:01:04 ERROR pigstats.PigStatsUtil: 1 map reduce job(s) failed! 12/04/05 10:01:04 INFO pigstats.PigStats: Script Statistics: HadoopVersion PigVersion UserId StartedAt FinishedAt Features 0.20.2-cdh3u3 0.8.1-cdh3u3 cchuang 2012-04-05 10:00:34 2012-04-05 10:01:04 GROUP_BY,ORDER_BY Some jobs have failed! Stop running all dependent jobs Job Stats (time in seconds): JobId Maps Reduces MaxMapTime MinMapTIme AvgMapTime MaxReduceTime MinReduceTime AvgReduceTime Alias Feature Outputs job_local_0001 0 0 0 0 0 0 0 0 all_influence_scores,grouped_user_similarity,simplified_user_similarity,user_similarity GROUP_BY job_local_0002 0 0 0 0 0 0 0 0 grouped_influence_scores,influence_scores GROUP_BY,COMBINER job_local_0003 0 0 0 0 0 0 0 0 ordered_influence_scores SAMPLER Failed Jobs: JobId Alias Feature Message Outputs job_local_0004 ordered_influence_scores ORDER_BY Message: Job failed! Error - NA /tmp/cc-test-results-1, Input(s): Successfully read 0 records from: "/tmp/sample-sim-score-results-31/part-r-00000" Output(s): Failed to produce result in "/tmp/cc-test-results-1" Counters: Total records written : 0 Total bytes written : 0 Spillable Memory Manager spill count : 0 Total bags proactively spilled: 0 Total records proactively spilled: 0 Job DAG: job_local_0001 -> job_local_0002, job_local_0002 -> job_local_0003, job_local_0003 -> job_local_0004, job_local_0004 12/04/05 10:01:04 INFO mapReduceLayer.MapReduceLauncher: Some jobs have failed! Stop running all dependent jobs

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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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  • ASP .NET 2.0 C# AjaxPro RegisterTypeForAjax

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  • How to optimize this JSON/JQuery/Javascript function in IE7/IE8?

    - by melaos
    hi guys, i'm using this function to parse this json data but i find the function to be really slow in IE7 and slightly slow in IE8. basically the first listbox generate the main product list, and upon selection of the main list, it will populate the second list. this is my data: [{"ProductCategoryId":209,"ProductCategoryName":"X-Fi","ProductSubCategoryId":668,"ProductSubCategoryName":"External Solutions","ProductId":15913,"ProductName":"Creative Xmod","ProductServiceLifeId":1},{"ProductCategoryId":209,"ProductCategoryName":"X-Fi","ProductSubCategoryId":668,"ProductSubCategoryName":"External Solutions","ProductId":15913,"ProductName":"Creative Xmod","ProductServiceLifeId":1},{"ProductCategoryId":209,"ProductCategoryName":"X-Fi","ProductSubCategoryId":668,"ProductSubCategoryName":"External Solutions","ProductId":18094,"ProductName":"Sound Blaster Wireless Receiver","ProductServiceLifeId":1},{"ProductCategoryId":209,"ProductCategoryName":"X-Fi","ProductSubCategoryId":668,"ProductSubCategoryName":"External Solutions","ProductId":16185,"ProductName":"Xdock Wireless","ProductServiceLifeId":1},{"ProductCategoryId":209,"ProductCategoryName":"X-Fi","ProductSubCategoryId":668,"ProductSubCategoryName":"External Solutions","ProductId":16186,"ProductName":"Xmod Wireless","ProductServiceLifeId":1}] and these are the functions that i'm using: //Three Product Panes function function populateMainPane() { $.getJSON('/Home/ThreePaneProductData/', function(data) { products = data; alert(JSON.stringify(products)); var prodCategory = {}; for (i = 0; i < products.length; i++) { prodCategory[products[i].ProductCategoryId] = products[i].ProductCategoryName; } //end for //take only unique product category to be used var id = 0; for (id in prodCategory) { if (prodCategory.hasOwnProperty(id)) { $(".LBox1").append("<option value='" + id + "'>" + prodCategory[id] + "</option>"); //alert(prodCategory[id]); } } var url = document.location.href; var parms = url.substring(url.indexOf("?") + 1).split("&"); for (var i = 0; i < parms.length; i++) { var parm = parms[i].split("="); if (parm[0].toLowerCase() == "pid") { $(".PanelProductReg").show(); var nProductIds = parm[1].split(","); for (var k = 0; k < nProductIds.length; k++) { var nProductId = parseInt(nProductIds[k], 10); for (var j = 0; j < products.length; j++) { if (nProductId == parseInt(products[j].ProductId, 10)) { addProductRow(nProductId, products[j].ProductName); j = products.length; } } //end for } } } }); } //end function function populateSubCategoryPane() { var subCategory = {}; for (var i = 0; i < products.length; i++) { if (products[i].ProductCategoryId == $('.LBox1').val()) subCategory[products[i].ProductSubCategoryId] = products[i].ProductSubCategoryName; } //end for //clear off the list box first $(".LBox2").html(""); var id = 0; for (id in subCategory) { if (subCategory.hasOwnProperty(id)) { $(".LBox2").append("<option value='" + id + "'>" + subCategory[id] + "</option>"); //alert(prodCategory[id]); } } } //end function is there anything i can do to optimize this or is this a known browser issue?

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