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  • MS Analysis Services OLAP API for Python

    - by Kaloyan Todorov
    I am looking for a way to connect to a MS Analysis Services OLAP cube, run MDX queries, and pull the results into Python. In other words, exactly what Excel does. Is there a solution in Python that would let me do that? Someone with a similar question going pointed to Django's ORM. As much as I like the framework, this is not what I am looking for. I am also not looking for a way to pull rows and aggregate them -- that's what Analysis Services is for in the first place. Ideas? Thanks.

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  • Data structure for pattern matching.

    - by alvonellos
    Let's say you have an input file with many entries like these: date, ticker, open, high, low, close, <and some other values> And you want to execute a pattern matching routine on the entries(rows) in that file, using a candlestick pattern, for example. (See, Doji) And that pattern can appear on any uniform time interval (let t = 1s, 5s, 10s, 1d, 7d, 2w, 2y, and so on...). Say a pattern matching routine can take an arbitrary number of rows to perform an analysis and contain an arbitrary number of subpatterns. In other words, some patterns may require 4 entries to operate on. Say also that the routine (may) later have to find and classify extrema (local and global maxima and minima as well as inflection points) for the ticker over a closed interval, for example, you could say that a cubic function (x^3) has the extrema on the interval [-1, 1]. (See link) What would be the most natural choice in terms of a data structure? What about an interface that conforms a Ticker object containing one row of data to a collection of Ticker so that an arbitrary pattern can be applied to the data. What's the first thing that comes to mind? I chose a doubly-linked circular linked list that has the following methods: push_front() push_back() pop_front() pop_back() [] //overloaded, can be used with negative parameters But that data structure seems very clumsy, since so much pushing and popping is going on, I have to make a deep copy of the data structure before running an analysis on it. So, I don't know if I made my question very clear -- but the main points are: What kind of data structures should be considered when analyzing sequential data points to conform to a pattern that does NOT require random access? What kind of data structures should be considered when classifying extrema of a set of data points?

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  • need explanation on amortization in algorithm

    - by Pradeep
    I am a learning algorithm analysis and came across a analysis tool for understanding the running time of an algorithm with widely varying performance which is called as amortization. The autor quotes " An array with upper bound of n elements, with a fixed bound N, on it size. Operation clear takes O(n) time, since we should dereference all the elements in the array in order to really empty it. " The above statement is clear and valid. Now consider the next content: "Now consider a series of n operations on an initially empty array. if we take the worst case viewpoint, the running time is O(n^2), since the worst case of a sigle clear operation in the series is O(n) and there may be as many as O(n) clear operations in the series." From the above statement how is the time complexity O(n^2)? I did not understand the logic behind it. if 'n' operations are performed how is it O(n ^2)? Please explain what the autor is trying to convey..

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  • Common request: export #Tabular model and data to #PowerPivot

    - by Marco Russo (SQLBI)
    I received this request in many courses, messages and also forum discussions: having an Analysis Services Tabular model, it would be nice being able to extract a correspondent PowerPivot data model. In order of priority, here are the specific feature people (including me) would like to see: Create an empty PowerPivot workbook with the same data model of a Tabular model Change the connections of the tables in the PowerPivot workbook extracting data from the Tabular data model Every table should have an EVALUATE ‘TableName’ query in DAX Apply a filter to data extracted from every table For example, you might want to extract all data for a single country or year or customer group Using the same technique of applying filter used for role based security would be nice Expose an API to automate the process of creating a PowerPivot workbook Use case: prepare one workbook for every employee containing only its data, that he can use offline Common request for salespeople who want a mini-BI tool to use in front of the customer/lead/supplier, regardless of a connection available This feature would increase the adoption of PowerPivot and Tabular (and, therefore, Business Intelligence licenses instead of Standard), and would probably raise the sales of Office 2013 / Office 365 driven by ISV, who are the companies who requests this feature more. If Microsoft would do this, it would be acceptable it only works on Office 2013. But if a third-party will do that, it will make sense (for their revenues) to cover both Excel 2010 and Excel 2013. Another important reason for this feature is that the “Offline cube” feature that you have in Excel is not available when your PivotTable is connected to a Tabular model, but it can only be used when you connect to Analysis Services Multidimensional. If you think this is an important features, you can vote this Connect item.

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  • Parallelize incremental processing in Tabular #ssas #tabular

    - by Marco Russo (SQLBI)
    I recently came in a problem trying to improve the parallelism of Tabular processing. As you know, multiple tables can be processed in parallel, whereas the processing of several partitions within the same table cannot be parallelized. When you perform an incremental update by adding only new rows to existing table, what you really do is adding rows to a partition, so adding rows to many tables means adding rows to several partitions. The particular condition you have in this case is that every partition in which you add rows belongs to a different table. Adding rows implies using the ProcessAdd command; its QueryBinding parameter specifies a SQL syntax to read new rows, otherwise the original query specified for the partition will be used, and it could generate duplicated data if you don’t have a dynamic behavior on the SQL side. If you create the required XMLA code manually, you will find that the QueryBinding node that should be part of the ProcessAdd command has to be moved out from ProcessAdd in case you are using a Batch command with more than one Process command (which is the reason why you want to use a single batch: run multiple process operations in parallel!). If you use AMO (Analysis Management Objects) you will find that this combination is not supported, even if you don’t have a syntax error compiling the code, but you might obtain this error at execution time: The syntax for the 'Process' command is incorrect. The 'Bindings' keyword cannot appear under a 'Process' command if the 'Process' command is a part of a 'Batch' command and there are more than one 'Process' commands in the 'Batch' or the 'Batch' command contains any out of line related information. In this case, the 'Bindings' keyword should be a part of the 'Batch' command only. If this is happening to you, the best solution I’ve found is manipulating the XMLA code generated by AMO moving the Binding nodes in the right place. A more detailed description of the issue and the code required to send a correct XMLA batch to Analysis Services is available in my article Parallelize ProcessAdd with AMO. By the way, the same technique (and code) can be used also if you have the same problem in a Multidimensional model.

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  • Android Signal analysis + some filters.

    - by Profete162
    Hello, as the world cup is the main sport event and the Vuvuzelas are the most annoying sound in the world, I had an idea to remove them definitively by reading this new ( http://www.popsci.com/diy/article/2010-06/simple-software-can-filter-out-vuvuzela-whine) that told us that the sound has some frequencies at 233Hz + 466,932,1864Hz. I have already made a lot of Android application by myself but never touching the signal analysis and filtering part, so here are a few questions, I do not ask for precise answer but maybe links and tutorial to find something to work on. I guess that a new Android phone has the CPU and power to make real-time filtering. 1) How can I intercept the sound coming from the Jack microphone - Line-IN plug- ( I plan to link my TV to my phone with Jack to Jack plug). My question is totally software and coding, I have all the wires and adapters to plug a jack into my android phone Line IN. 2) Are there some Fourier analysis librairies, may I have a look to Java libraries on the web and import them to my Android project? I really apologize because my question seem not precise, but I think that would be something great. Thank you for your answers.

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  • Statistical analysis on large data set to be published on the web

    - by dassouki
    I have a non-computer related data logger, that collects data from the field. This data is stored as text files, and I manually lump the files together and organize them. The current format is through a csv file per year per logger. Each file is around 4,000,000 lines x 7 loggers x 5 years = a lot of data. some of the data is organized as bins item_type, item_class, item_dimension_class, and other data is more unique, such as item_weight, item_color, date_collected, and so on ... Currently, I do statistical analysis on the data using a python/numpy/matplotlib program I wrote. It works fine, but the problem is, I'm the only one who can use it, since it and the data live on my computer. I'd like to publish the data on the web using a postgres db; however, I need to find or implement a statistical tool that'll take a large postgres table, and return statistical results within an adequate time frame. I'm not familiar with python for the web; however, I'm proficient with PHP on the web side, and python on the offline side. users should be allowed to create their own histograms, data analysis. For example, a user can search for all items that are blue shipped between week x and week y, while another user can search for sort the weight distribution of all items by hour for all year long. I was thinking of creating and indexing my own statistical tools, or automate the process somehow to emulate most queries. This seemed inefficient. I'm looking forward to hearing your ideas Thanks

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  • Willy Rotstein on Analytics and Social Media in Retail

    - by sarah.taylor(at)oracle.com
    Recently I came across a presentation from Dan Zarrella on "The Science of Retweets. (http://www.slideshare.net/HubSpot/the-science-of-retweets-with-dan-zarrella). It is an insightful, fact-based analysis of how tweets propagate and what makes them successful. The analysis is of course very interesting for those of us interested Tweeting. However, what really caught my attention is how well it illustrates, form a very different angle, some of the issues I am discussing with retailers these days. In particular the opportunities that e-commerce and social media open to those retailers with the appetite and vision to tackle the associated analytical challenges. And these challenges are of course not straightforward.   In his presentation Dan introduces the concept of Observability, I haven't had the opportunity to discuss with Dan his specific definition for the term. However, in practical retail terms, I would say that it means that through social media (and other web channels such as search) we can analyze and track processes by measuring Indicators that were not measurable before. The focus is in identifying patterns across a large number of consumers rather than what a particular individual "Likes".   The potential impact for retailers is huge. It opens the opportunity to monitor changes in consumer preference  and plan the business accordingly. And you can do this almost "real time" rather than through infrequent surveys that provide a "rear view" picture of your consumer behaviour. For instance, you could envision identifying when a particular set of fashion styles are breaking out from the pack, and commit a re-buy. Or you could monitor when the preference for a specific mobile device has declined and hence markdowns should be considered; or how demand for a specific ready-made food typically flows across regions and manage the inventory accordingly. Search, blogging, website and store data may need to be considered in identifying these trends. The data volumes involved are huge (check Andrea Morgan's recent post on "Big Data" in retail) but so are the benefits. As Andrea says, for the first time we can start getting insight into "Why" the business is performing in a certain way rather than just reporting on what is happening. And it is not just about the data volumes. Tackling the challenge also calls for integrated planning systems that can bring data and insight into the context of the Decision Making process Buyers, Merchandisers and Supply Chain managers are following. I strongly believe that only when data and process come together you can move from the anecdotal to systematically improving business performance.   I would love to hear your opinions on these trends and where you think Retail is heading to exploit these topics - please email me: [email protected]

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  • #SSAS #Tabular Workshop and Community Events in Netherlands and Denmark

    - by Marco Russo (SQLBI)
    Next week I will finally start the roadshow of the SSAS Tabular Workshop, a 2-day seminar about the new BISM Tabular model for Analysis Services that has been introduced in SQL Server 2012. During these roadshows, we always try to arrange some speeches at local community events in the evening - we already defined for Copenhagen, we have some logistic issue in Amsterdam that we're trying to solve. Here is the timetable: Netherlands SSAS Workshop in Amsterdam, NL – April 16-17, 2012 2-day seminar, I and Alberto will be the trainers for this event, register here We're trying to manage a Community event but we still don't have a confirmation, stay tuned        Denmark SSAS Workshop in Copenhagen, DK – April 26-27, 2012 2-day seminar, I and Alberto will be the trainers for this event, register here Community event on April 26, 2012 This event will run in Hellerup, at Microsoft venue All details available here: http://msbip.dk/events/26/msbip-mode-nr-5/ People from Sweden are welcome! Just register to this private group on LinkedIn in order to announce your presence, so we’ll know how many people will attend In community events we’ll deliver two speeches – here are the descriptions: Inside xVelocity (VertiPaq) PowerPivot and BISM Tabular models in Analysis Services share a great columnar-based database engine called xVelocity in-memory analytics engine (VertiPaq). If you want to improve performance and optimize memory used, you have to understand some basic principles about how this engine works, how data is compressed, and how you can design a data model for better optimization. Prepare yourself to change your mind. xVelocity optimization techniques might seem counterintuitive and are absolutely different than OLAP and SQL ones! Choosing between Tabular and Multidimensional You have a new project and you have to make an important decision upfront. Should you use Tabular or Multidimensional? It is not easy to answer, because sometime there is a clear choice, but most of the times both decisions might be correct, at least at the beginning. In this session we’ll help you making an informed decision, correctly evaluating pros and cons of each one according to common scenarios, considering both short-term and long-term consequences of your choice. I hope to meet many people in this first dates. We have many other events coming in May and June, including an online event (for US time zones), and you can also attend our PreCon Day at TechEd US in Orland (PRC06) or TechEd Europe in Amsterdam. I’ll be a good customer for airline companies in the next three months! I’m just sorry that I hadn’t time to write other articles in the last month, but I’m accumulating material that I will need to write down during some flight – stay tuned…

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  • RoboCopy Log File Analysis

    - by BobJim
    Is it possible to analyse the log text file outputted from RoboCopy and extract the lines which are defined as "New Dir" and "Extra Dir"? I would like the line from the log contain all the details returned regarding this "New Dir" or "Extra Dir" The reason for completing this task is to understand how two folder structures have change over time. One version has been kept internally at the parent company, the second has been used by a consultancy. For your information I am using Windows 7.

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  • Excel techniques for perfmon csv log file analysis

    - by Aszurom
    I have perfmon running against several servers, where I'm outputting to a .csv file data like CPU %time, memory bytes free, hard disk I/O metrics like s/write and writes/s. The ones graphing the SQL servers are also collecting SQL stats. The web servers are collecting .Net relevant stuff. I am aware of PAL, and used it as a template of what data to capture based on server type actually. I just don't think the output it generates is detailed or flexible enough - but it does a pretty remarkable job of parsing logs and making graphs. I'm borderline incompetent with Excel, so I'm hoping to be directed to some knowledge of how to take a perfmon output .csv and mine it in Excel to produce some numbers that are meaningful to me as a sysadmin. I could of course just pick a range of data and assemble a graph out of that and look for spikes and trends, but I'm convinced there is some technique to this that makes it more manageable than looking at a monsterous spreadsheet of numbers and trying to make graphs of it. Plus, it's pretty time consuming and not something I can do as a "take a glance at the servers" sort of routine. I'm graphing CPU, disk use, network b/sec, etc. in Cacti as well, which is nice for seeing big trends. The problem is that it is 5 minute averages, so a server could have a problem but it's intermittent and washes out in a 5 min average. What do you do with perfmon data that I could learn from?

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  • Linux installation analysis

    - by blunders
    "Ending company IT Admin relationship" has a good checklist for taking over an existing IT system, but I'm wondering as it relates to Linux: What is the most effective way to assess the scope of existing custom configurations, installs, scripts, etc done? Is there any software that will check if the kernel, system files, etc mirror the default files for the version installed? At this point I don't know what distro of Linux the server (though using Netcraft I do know the server appears to be Linux) -- so it's possible without knowing that information that this would be a hard question to answer.

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  • MySql Data Loss - post mortem analysis - RackSpace Cloud Server

    - by marfarma
    After a recent 'emergency migration' of a RS cloud server, the mysql databases on our server snapshot image proved to be days out of date from the backup date. And yet files that were uploaded through the impacted webapp had been written to the file system. Related metadata that was written to the database was lost, but the files themselves were backed-up. Once I was able to manually access the mysql data files before the mysql server started (server was configured to start mysql on boot), I was able to see that the update time for ib_logfile1, ib_logfile0 and ibdata1 was days old. As with this poster, mysql data loss after server crash, it's as if some caching controller had told the OS / mysql server that it had committed data that was still in cache, and it was lost instead of flushed. I can't quite wrap my head around how the uploaded files got written but the database data did not. I would have thought that any cache would have flushed system wide, rather than process by process. Any suggestions as to how this might have happened?

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  • FAT filesystem analysis tool

    - by Andy
    I have a dump a FAT file system. Is there a windows tool I can use to analyse it, including: Provide basic information (sector size etc.) Validate the file system, basic corruption checking Allow the files and directory structure to be viewed and possibly edited (i.e mounting as a windows partition) Thanks, Andy

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  • Windows File System Analysis

    - by bouvierr
    I am looking for a FREE tool to perform analyses on the NTFS file system of my Windows 7 PC. I want to easily see the amount of data distributed throught out the entire file system. The following applications seem very good, but they are not free and probably overkill for my requirements: FolderSizes 5 MailMeter Windows File System Reporting Tool I am aware that some applications (like Folder Size 2.5) can add a column in Windows Explorer to show the size of each folder, but I am looking for something more like a reporting tool. Thank you for your suggestions.

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  • Server hang - data loss on reboot, post mortem analysis

    - by rovangju
    A development server I'm responsible for (ext3 on raid 5 w/Debian Squeeze) froze up over the weekend and I was forced to reset it, as in unresponsive from KVM/physical keyboard access, no eth devices responding, etc. Not even the backup process ran (Figures, the one time I don't check for confirmation) So after the reset, it turns out that every trace of disk IO activity that should have happened for a period of ~24H is completely gone. The log files have a big gap in the dates and times. As if the writes were never committed to disk, no processes seemed to have run. Luckily it was a weekend and nothing of value would have been lost and I don't suspect a hack. What can I do in post mortem to this event - to prevent it from ever happening again? I've seen this happen before on a completely different machine running FreeBSD. I am rounding up the disk checking tools right now - but there must be more going on! Mount options: /dev/sda1 on / type ext3 (rw,errors=remount-ro) Kernel: Linux dev 2.6.32-5-686-bigmem Disk/Inodes: 13%/3%

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  • Forensic Analysis of the OOM-Killer

    - by Oddthinking
    Ubuntu's Out-Of-Memory Killer wreaked havoc on my server, quietly assassinating my applications, sendmail, apache and others. I've managed to learn what the OOM Killer is, and about its "badness" rules. While my machine is small, my applications are even smaller, and typically only half of my physical memory is in use, let alone swap-space, so I was surprised. I am trying to work out the culprit, but I don't know how to read the OOM-Killer logs. Can anyone please point me to a tutorial on how to read the data in the logs (what are ve, free and gen?), or help me parse these logs? Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): selecting to kill, queued 0, seq 1, exc 2326 0 goal 2326 0... Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): task ebb0c6f0, thg d33a1b00, sig 1 Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): selected 1, signalled 1, queued 1, seq 1, exc 2326 0 red 61795 745 Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): selecting to kill, queued 0, seq 2, exc 122 0 goal 383 0... Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): task ebb0c6f0, thg d33a1b00, sig 1 Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): selected 1, signalled 1, queued 1, seq 2, exc 383 0 red 61795 745 Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): task ebb0c6f0, thg d33a1b00, sig 2 Apr 20 20:03:27 EL135 kernel: OOM killed process watchdog (pid=14490, ve=13516) exited, free=43104 gen=24501. Apr 20 20:03:27 EL135 kernel: OOM killed process tail (pid=4457, ve=13516) exited, free=43104 gen=24502. Apr 20 20:03:27 EL135 kernel: OOM killed process ntpd (pid=10816, ve=13516) exited, free=43104 gen=24503. Apr 20 20:03:27 EL135 kernel: OOM killed process tail (pid=27401, ve=13516) exited, free=43104 gen=24504. Apr 20 20:03:27 EL135 kernel: OOM killed process tail (pid=29009, ve=13516) exited, free=43104 gen=24505. Apr 20 20:03:27 EL135 kernel: OOM killed process apache2 (pid=10557, ve=13516) exited, free=49552 gen=24506. Apr 20 20:03:27 EL135 kernel: OOM killed process apache2 (pid=24983, ve=13516) exited, free=53117 gen=24507. Apr 20 20:03:27 EL135 kernel: OOM killed process apache2 (pid=29129, ve=13516) exited, free=68493 gen=24508. Apr 20 20:03:27 EL135 kernel: OOM killed process sendmail-mta (pid=941, ve=13516) exited, free=68803 gen=24509. Apr 20 20:03:27 EL135 kernel: OOM killed process tail (pid=12418, ve=13516) exited, free=69330 gen=24510. Apr 20 20:03:27 EL135 kernel: OOM killed process python (pid=22953, ve=13516) exited, free=72275 gen=24511. Apr 20 20:03:27 EL135 kernel: OOM killed process apache2 (pid=6624, ve=13516) exited, free=76398 gen=24512. Apr 20 20:03:27 EL135 kernel: OOM killed process python (pid=23317, ve=13516) exited, free=94285 gen=24513. Apr 20 20:03:27 EL135 kernel: OOM killed process tail (pid=29030, ve=13516) exited, free=95339 gen=24514. Apr 20 20:03:28 EL135 kernel: OOM killed process apache2 (pid=20583, ve=13516) exited, free=101663 gen=24515. Apr 20 20:03:28 EL135 kernel: OOM killed process logger (pid=12894, ve=13516) exited, free=101694 gen=24516. Apr 20 20:03:28 EL135 kernel: OOM killed process bash (pid=21119, ve=13516) exited, free=101849 gen=24517. Apr 20 20:03:28 EL135 kernel: OOM killed process atd (pid=991, ve=13516) exited, free=101880 gen=24518. Apr 20 20:03:28 EL135 kernel: OOM killed process apache2 (pid=14649, ve=13516) exited, free=102748 gen=24519. Apr 20 20:03:28 EL135 kernel: OOM killed process grep (pid=21375, ve=13516) exited, free=132167 gen=24520. Apr 20 20:03:57 EL135 kernel: kill_signal(13516.0): selecting to kill, queued 0, seq 4, exc 4215 0 goal 4826 0... Apr 20 20:03:57 EL135 kernel: kill_signal(13516.0): task ede29370, thg df98b880, sig 1 Apr 20 20:03:57 EL135 kernel: kill_signal(13516.0): selected 1, signalled 1, queued 1, seq 4, exc 4826 0 red 189481 331 Apr 20 20:03:57 EL135 kernel: kill_signal(13516.0): task ede29370, thg df98b880, sig 2 Apr 20 20:04:53 EL135 kernel: kill_signal(13516.0): selecting to kill, queued 0, seq 5, exc 3564 0 goal 3564 0... Apr 20 20:04:53 EL135 kernel: kill_signal(13516.0): task c6c90110, thg cdb1a100, sig 1 Apr 20 20:04:53 EL135 kernel: kill_signal(13516.0): selected 1, signalled 1, queued 1, seq 5, exc 3564 0 red 189481 331 Apr 20 20:04:53 EL135 kernel: kill_signal(13516.0): task c6c90110, thg cdb1a100, sig 2 Apr 20 20:07:14 EL135 kernel: kill_signal(13516.0): selecting to kill, queued 0, seq 6, exc 8071 0 goal 8071 0... Apr 20 20:07:14 EL135 kernel: kill_signal(13516.0): task d7294050, thg c03f42c0, sig 1 Apr 20 20:07:14 EL135 kernel: kill_signal(13516.0): selected 1, signalled 1, queued 1, seq 6, exc 8071 0 red 189481 331 Apr 20 20:07:14 EL135 kernel: kill_signal(13516.0): task d7294050, thg c03f42c0, sig 2 Watchdog is a watchdog task, that was idle; nothing in the logs to suggest it had done anything for days. Its job is to restart one of the applications if it dies, so a bit ironic that it is the first to get killed. Tail was monitoring a few logs files. Unlikely to be consuming memory madly. The apache web-server only serves pages to a little old lady who only uses it to get to church on Sundays a couple of developers who were in bed asleep, and hadn't visited a page on the site for a few weeks. The only traffic it might have had is from the port-scanners; all the content is password-protected and not linked from anywhere, so no spiders are interested. Python is running two separate custom applications. Nothing in the logs to suggest they weren't humming along as normal. One of them was a relatively recent implementation, which makes suspect #1. It doesn't have any data-structures of any significance, and normally uses only about 8% of the total physical RAW. It hasn't misbehaved since. The grep is suspect #2, and the one I want to be guilty, because it was a once-off command. The command (which piped the output of a grep -r to another grep) had been started at least 30 minutes earlier, and the fact it was still running is suspicious. However, I wouldn't have thought grep would ever use a significant amount of memory. It took a while for the OOM killer to get to it, which suggests it wasn't going mad, but the OOM killer stopped once it was killed, suggesting it may have been a memory-hog that finally satisfied the OOM killer's blood-lust.

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  • Confusion about TCP packet analysis terms

    - by Berkay
    I'm analyzing our network and have some confusion about the terms: this is the 2-packet output from source to destination. from these i have to get some features as describe, pls make me clear... packets with at least a bytes of TCP data payload: it seems tcp.len0; The minimum segment size (confusion is headers are included or or not) The average segment size observed during the lifetime of the connection, the definition: is calculated as the value reported in the actual data bytes divided by the actual data pkts reported. Total bytes in IP packets, should be ip_len value. Total bytes in (Ethernet) The total number of bytes sent probably related to frame.len and frame.cap_len these two terms are describes as, also make me clear about these two terms. frame.cap_len: Frame length stored into the capture file frame.len: Frame length on the wire

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  • Windows Handling Piped Comands Error Redirection

    - by jpmartins
    Warning: I am no expert on building scripts, and sorry for lousy English. In an case of generating a CSV from a database query I'm using the following commands. ... CALL java.exe -classpath ... com.xigole.util.sql.Jisql -user dmfodbc -pf pwd.file -driver com.sybase.jdbc3.jdbc.SybDriver -cstring %constr% -c ; -input 42.sql -formatter csv -delimiter ; 2%LOGFILE% | CALL grep -v -e "SELECT right" -e "executing: " -e " rows affect" %FicheiroR% 2%LOGFILE% ... I'm using windows implementation of grep. The 2%LOGFILE% in both java and grep command is causing an error message indicating the file is being use by another process. The Ugly workaround i have came up with is to put grep error redirect to a temporary %LOGFILE%.aux java ... | grep ... 2%LOGFILE%.aux type %LOGFILE%.aux % %LOGFILE% del %LOGFILE%.aux What is a better solution?

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  • Windows Disk I/O Analysis

    - by Jonathon
    It appears that we are having a problem with the disk i/o speed on our Windows 2003 Enterprise Edition server (64-bit). As we were initializing a database that created two 1G tablespaces on 3 different machines, it became obvious that the two smaller machines (each 32-bit Windows 2003 Standard Edition with less RAM) killed the larger machine when creating the files. The larger machine took 10x as long to create the tablespaces than did the other machines. Now, I am left wondering how that could be. What programs or scripts would you guys recommend for tracking down the I/O problem? I think the issue may be with the controller card (all boxes are hardware RAID 10, but have different controller cards), but I would like to check the actual disk I/O speed as well, so I have some hard numbers to work with. Any help would be appreciated.

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  • Ubuntu 12.04 crash analysis - strange binary data on all open files at the moment of crash

    - by lanbo
    A couple of hours ago we got a system crash on Ubuntu 12.04. We checked all the log files and there is nothing suspicious to blame to. Last stuff that was logged was some dovecot activity. There are no kernel panic messages. Nothing. It is a new server (new hardware) we are testing before production. And because it is new hard, I'm suspicious the problem may be due to some faulty hardware. We already run memtester with no problem detected. I'll be happy to hear from other hardware testing tools (the machine has SSD). Anyway, the thing I wanted to ask you is a different one. The strange thing is on every open file at the moment of the crash we found the next sequence of symbols was written into them: "@^@^@^@^@^@^@...". For example, on the syslog log file we got: Apr 16 15:53:56 odyssey dovecot: pop3-login: Aborted login (auth failed, 1 attempts): user=<info>, method=PLAIN, rip=46.29.255.73, lip=5.9.58.177 ^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^@^ [these continues for about 1000 chars...] ^@^@^@^@Apr 16 15:55:12 odyssey kernel: imklog 5.8.6, log source = /proc/kmsg started. We got all these symbols in all open files. These include: syslog, mail.log, kern.log, ... But also on some logs that are output by php scripts run in CRONs from user accounts (not root). So, any idea why all open files got these characters written during the crash? This is pretty bad since the crash corrupted many files (we don't even know which other ones may be affected). We are suspicious that all open files (in write mode maybe) at the moment of the crash got all these symbols inserted. Why is that? BTW [in case it helps], the system automatically rebooted after the crash but Apache did not start. There were not traces in /var/apache2/*log why apache did not start. After running a "service apache2 start" it started with no problems. Also, we rebooted the machine manually and Apache also started on reboot. But it did not start after the crash and no errors were reported. Thanks guys!

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  • MySQL Non Index Queries Analysis

    - by Markii
    I'm using the log queries not using index but it logs all that use indexes but just more advanced or using IFs. Is there a parser or a program out there that can analyze the log and give me a literal output of saying "table.column should be a index" Thanks

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