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  • PostgreSQL - Why are some queries on large datasets so incredibly slow

    - by Brad Mathews
    Hello, I have two types of queries I run often on two large datasets. They run much slower than I would expect them to. The first type is a sequential scan updating all records: Update rcra_sites Set street = regexp_replace(street,'/','','i') rcra_sites has 700,000 records. It takes 22 minutes from pgAdmin! I wrote a vb.net function that loops through each record and sends an update query for each record (yes, 700,000 update queries!) and it runs in less than half the time. Hmmm.... The second type is a simple update with a relation and then a sequential scan: Update rcra_sites as sites Set violations='No' From narcra_monitoring as v Where sites.agencyid=v.agencyid and v.found_violation_flag='N' narcra_monitoring has 1,700,000 records. This takes 8 minutes. The query planner refuses to use my indexes. The query runs much faster if I start with a set enable_seqscan = false;. I would prefer if the query planner would do its job. I have appropriate indexes, I have vacuumed and analyzed. I optimized my shared_buffers and effective_cache_size best I know to use more memory since I have 4GB. My hardware is pretty darn good. I am running v8.4 on Windows 7. Is PostgreSQL just this slow? Or am I still missing something? Thanks! Brad

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  • C# - parse content away from structure in a binary file

    - by Jeff Godfrey
    Using C#, I need to read a packed binary file created using FORTRAN. The file is stored in an "Unformatted Sequential" format as described here (about half-way down the page in the "Unformatted Sequential Files" section): http://www.tacc.utexas.edu/services/userguides/intel8/fc/f_ug1/pggfmsp.htm As you can see from the URL, the file is organized into "chunks" of 130 bytes or less and includes 2 length bytes (inserted by the FORTRAN compiler) surrounding each chunk. So, I need to find an efficient way to parse the actual file payload away from the compiler-inserted formatting. Once I've extracted the actual payload from the file, I'll then need to parse it up into its varying data types. That'll be the next exercise. My first thoughts are to slurp up the entire file into a byte array using File.ReadAllBytes. Then, just iterate through the bytes, skipping the formatting and transferring the actual data to a second byte array. In the end, that second byte array should contain the actual file contents minus all the formatting, which I'd then need to go back through to get what I need. As I'm fairly new to C#, I thought there might be a better, more accepted way of tackling this. Also, in case it's helpful, these files could be fairly large (say 30MB), though most will be much smaller...

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  • verilog / systemverilog -- What is the behavior of blocking statements across two always blocks?

    - by miles.sherman
    I am wondering about the behavior of the below code. There are two always blocks, one is combinational to calculate the next_state signal, the other is sequential which will perform some logic and determine whether or not to shutdown the system. It does this by setting the shutdown_now signal high and then calling state <= next_state. My question is if the conditions become true that the shutdown_now signal is set (during clock cycle n) in a blocking manner before the state <= next_state line, will the state during clock cycle n+1 be SHUTDOWN or RUNNING? In other words, does the shutdown_now = 1'b1 line block across both state machines since the state signal is dependent on it through the next_state determination? enum {IDLE, RUNNING, SHUTDOWN} state, next_state; logic shutdown_now; // State machine (combinational) always_comb begin case (state) IDLE: next_state <= RUNNING; RUNNING: next_state <= shutdown ? SHUTDOWN : RUNNING; SHUTDOWN: next_state <= SHUTDOWN; default: next_state <= SHUTDOWN; endcase end // Sequential Behavior always_ff @ (posedge clk) begin // Some code here if (/*some condition) begin shutdown_now = 1'b0; end else begin shutdown_now = 1'b1; end state <= next_state; end

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  • How to parameterize a path in ANT?

    - by strelokstrelok
    I have the following defined in a file called build-dependencies.xml <?xml version="1.0" encoding="UTF-8"?> <project name="build-dependencies"> ... <path id="common-jars"> <fileset file="artifacts/project-1/jar/some*.jar" /> <fileset file="artifacts/project-2/jar/someother*.jar" /> </path> ... </project> I include it at the top of my build.xml file. Now I need to make the artifacts folder a parameter so it can be changed during execution of different targets. Having this... <?xml version="1.0" encoding="UTF-8"?> <project name="build-dependencies"> ... <path id="common-jars"> <fileset file="${artifacts}/project-1/jar/some*.jar" /> <fileset file="${artifacts}/project-2/jar/someother*.jar" /> </path> ... </project> ...and defining an "artifacts" property (and changing it) in the target does not work because it seems that the property substitution happens when the path is defined in build-dependencies.xml How can I solve this? One way I was thinking was to have a parameterized macro and call that before the path is actually used, but that seems not elegant. Something like this: <macrodef name="create-common-jars"> <attribute name="artifacts"/> <sequential> <path id="common-jars"> <fileset file="@{artifacts}/project-1/jar/some*.jar" /> <fileset file="@{artifacts}/project-2/jar/someother*.jar" /> </path> </sequential> </macrodef>

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  • parse content away from structure in a binary file

    - by Jeff Godfrey
    Using C#, I need to read a packed binary file created using FORTRAN. The file is stored in an "Unformatted Sequential" format as described here (about half-way down the page in the "Unformatted Sequential Files" section): http://www.tacc.utexas.edu/services/userguides/intel8/fc/f_ug1/pggfmsp.htm As you can see from the URL, the file is organized into "chunks" of 130 bytes or less and includes 2 length bytes (inserted by the FORTRAN compiler) surrounding each chunk. So, I need to find an efficient way to parse the actual file payload away from the compiler-inserted formatting. Once I've extracted the actual payload from the file, I'll then need to parse it up into its varying data types. That'll be the next exercise. My first thoughts are to slurp up the entire file into a byte array using File.ReadAllBytes. Then, just iterate through the bytes, skipping the formatting and transferring the actual data to a second byte array. In the end, that second byte array should contain the actual file contents minus all the formatting, which I'd then need to go back through to get what I need. As I'm fairly new to C#, I thought there might be a better, more accepted way of tackling this. Also, in case it's helpful, these files could be fairly large (say 30MB), though most will be much smaller...

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  • Using Ant how can I dex a directory of jars?

    - by cbeaudin
    I have a directory full of jars (felix bundles). I want to iterate through all of these jars and create dex'd versions. My intent is to deploy each of these dex'd jars as standalone apk's since they are bundles. Feel free to straighten me out if I am approaching this from the wrong direction. This first part is just to try and create a corresponding .dex file for each jar. However when I run this I am getting a "no resources specified" error coming out of Ant. Is this the right approach, or is there a simpler approach to just input a jar and output a dex'd version of that jar? The ${file} is valid as it is spitting out the name of the file in the echo command. <target name="dexBundles" description="Run dex on all the bundles"> <taskdef resource="net/sf/antcontrib/antlib.xml" classpath="${basedir}/libs/ant-contrib.jar" /> <echo>Starting</echo> <for param="file"> <path> <fileset dir="${pre.dex.dir}"> <include name="**/*.jar" /> </fileset> </path> <sequential> <echo message="@{file}" /> <echo>Converting jar file @{file} into ${post.dex.dir}/@{file}.class...</echo> <apply executable="${dx}" failonerror="true" parallel="true" verbose="true"> <arg value="--dex" /> <arg value="--output=${post.dex.dir}/${file}.dex" /> <arg path="@{file}" /> </apply> </sequential> </for> <echo>Finished</echo> </target>

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  • SQL indexes for "not equal" searches

    - by bortzmeyer
    The SQL index allows to find quickly a string which matches my query. Now, I have to search in a big table the strings which do not match. Of course, the normal index does not help and I have to do a slow sequential scan: essais=> \d phone_idx Index "public.phone_idx" Column | Type --------+------ phone | text btree, for table "public.phonespersons" essais=> EXPLAIN SELECT person FROM PhonesPersons WHERE phone = '+33 1234567'; QUERY PLAN ------------------------------------------------------------------------------- Index Scan using phone_idx on phonespersons (cost=0.00..8.41 rows=1 width=4) Index Cond: (phone = '+33 1234567'::text) (2 rows) essais=> EXPLAIN SELECT person FROM PhonesPersons WHERE phone != '+33 1234567'; QUERY PLAN ---------------------------------------------------------------------- Seq Scan on phonespersons (cost=0.00..18621.00 rows=999999 width=4) Filter: (phone <> '+33 1234567'::text) (2 rows) I understand (see Mark Byers' very good explanations) that PostgreSQL can decide not to use an index when it sees that a sequential scan would be faster (for instance if almost all the tuples match). But, here, "not equal" searches are really slower. Any way to make these "is not equal to" searches faster? Here is another example, to address Mark Byers' excellent remarks. The index is used for the '=' query (which returns the vast majority of tuples) but not for the '!=' query: essais=> EXPLAIN ANALYZE SELECT person FROM EmailsPersons WHERE tld(email) = 'fr'; QUERY PLAN ------------------------------------------------------------------------------------------------------------------------------------ Index Scan using tld_idx on emailspersons (cost=0.25..4010.79 rows=97033 width=4) (actual time=0.137..261.123 rows=97110 loops=1) Index Cond: (tld(email) = 'fr'::text) Total runtime: 444.800 ms (3 rows) essais=> EXPLAIN ANALYZE SELECT person FROM EmailsPersons WHERE tld(email) != 'fr'; QUERY PLAN -------------------------------------------------------------------------------------------------------------------- Seq Scan on emailspersons (cost=0.00..27129.00 rows=2967 width=4) (actual time=1.004..1031.224 rows=2890 loops=1) Filter: (tld(email) <> 'fr'::text) Total runtime: 1037.278 ms (3 rows) DBMS is PostgreSQL 8.3 (but I can upgrade to 8.4).

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  • How do I handle freeing unmanaged structures on application close?

    - by LostKaleb
    I have a C# project in which i use several unmanaged C++ functions. More so, I also have static IntPtr that I use as parameters for those functions. I know that whenever I use them, I should implement IDisposable in that class and use a destructor to invoke the Dispose method, where I free the used IntPtr, as is said in the MSDN page. public void Dispose() { Dispose(true); GC.SuppressFinalize(this); } private void Dispose(bool disposing) { // Check to see if Dispose has already been called. if (!this.disposed) { if (disposing) { component.Dispose(); } CloseHandle(m_InstanceHandle); m_InstanceHandle = IntPtr.Zero; disposed = true; } } [System.Runtime.InteropServices.DllImport("Kernel32")] private extern static Boolean CloseHandle(IntPtr handle); However, when I terminate the application, I'm still left with a hanging process in TaskManager. I believe that it must be related to the used of the MarshalAs instruction in my structures: [StructLayout(LayoutKind.Sequential, CharSet = CharSet.Ansi)] public struct SipxAudioCodec { [MarshalAs(UnmanagedType.ByValTStr, SizeConst=32)] public string CodecName; public SipxAudioBandwidth Bandwidth; public int PayloadType; } When I create such a structure should I also be careful to free the space it allocs using a destructor? [StructLayout(LayoutKind.Sequential, CharSet = CharSet.Ansi)] public struct SipxAudioCodec { [MarshalAs(UnmanagedType.ByValTStr, SizeConst=32)] public string CodecName; public SipxAudioBandwidth Bandwidth; public int PayloadType; ~SipxAudioCodec() { Marshal.FreeGlobal(something...); } }

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  • How do I handle freeing unmanaged structures in C# on application close?

    - by LostKaleb
    I have a C# project in which i use several unmanaged C++ functions. More so, I also have static IntPtr that I use as parameters for those functions. I know that whenever I use them, I should implement IDisposable in that class and use a destructor to invoke the Dispose method, where I free the used IntPtr, as is said in the MSDN page. public void Dispose() { Dispose(true); GC.SuppressFinalize(this); } private void Dispose(bool disposing) { // Check to see if Dispose has already been called. if (!this.disposed) { if (disposing) { component.Dispose(); } CloseHandle(m_InstanceHandle); m_InstanceHandle = IntPtr.Zero; disposed = true; } } [System.Runtime.InteropServices.DllImport("Kernel32")] private extern static Boolean CloseHandle(IntPtr handle); However, when I terminate the application, I'm still left with a hanging process in TaskManager. I believe that it must be related to the used of the MarshalAs instruction in my structures: [StructLayout(LayoutKind.Sequential, CharSet = CharSet.Ansi)] public struct SipxAudioCodec { [MarshalAs(UnmanagedType.ByValTStr, SizeConst=32)] public string CodecName; public SipxAudioBandwidth Bandwidth; public int PayloadType; } When I create such a structure should I also be careful to free the space it allocs using a destructor? [StructLayout(LayoutKind.Sequential, CharSet = CharSet.Ansi)] public struct SipxAudioCodec { [MarshalAs(UnmanagedType.ByValTStr, SizeConst=32)] public string CodecName; public SipxAudioBandwidth Bandwidth; public int PayloadType; ~SipxAudioCodec() { Marshal.FreeGlobal(something...); } } Thanks in advance!

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  • The best way to predict performance without actually porting the code?

    - by ardiyu07
    I believe there are people with the same experience with me, where he/she must give a (estimated) performance report of porting a program from sequential to parallel with some designated multicore hardwares, with a very few amount of time given. For instance, if a 10K LoC sequential program was given and executes on Intel i7-3770k (not vectorized) in 100 ms, how long would it take to run if one parallelizes the code to a Tesla C2075 with NVIDIA CUDA, given that all kinds of parallelizing optimization techniques were done? (but you're only given 2-4 days to report the performance? assume that you didn't know the algorithm at all. Or perhaps it'd be safer if we just assume that it's an impossible situation to finish the job) Therefore, I'm wondering, what most likely be the fastest way to give such performance report? Is it safe to calculate solely by the hardware's capability, such as GFLOPs peak and memory bandwidth rate? Is there a mathematical way to calculate it? If there is, please prove your method with the corresponding problem description and the algorithm, and also the target hardwares' specifications. Or perhaps there already exists such tool to (roughly) estimate code porting? (Please don't the answer: 'kill yourself is the fastest way.')

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  • Sorting Algorithms

    - by MarkPearl
    General Every time I go back to university I find myself wading through sorting algorithms and their implementation in C++. Up to now I haven’t really appreciated their true value. However as I discovered this last week with Dictionaries in C# – having a knowledge of some basic programming principles can greatly improve the performance of a system and make one think twice about how to tackle a problem. I’m going to cover briefly in this post the following: Selection Sort Insertion Sort Shellsort Quicksort Mergesort Heapsort (not complete) Selection Sort Array based selection sort is a simple approach to sorting an unsorted array. Simply put, it repeats two basic steps to achieve a sorted collection. It starts with a collection of data and repeatedly parses it, each time sorting out one element and reducing the size of the next iteration of parsed data by one. So the first iteration would go something like this… Go through the entire array of data and find the lowest value Place the value at the front of the array The second iteration would go something like this… Go through the array from position two (position one has already been sorted with the smallest value) and find the next lowest value in the array. Place the value at the second position in the array This process would be completed until the entire array had been sorted. A positive about selection sort is that it does not make many item movements. In fact, in a worst case scenario every items is only moved once. Selection sort is however a comparison intensive sort. If you had 10 items in a collection, just to parse the collection you would have 10+9+8+7+6+5+4+3+2=54 comparisons to sort regardless of how sorted the collection was to start with. If you think about it, if you applied selection sort to a collection already sorted, you would still perform relatively the same number of iterations as if it was not sorted at all. Many of the following algorithms try and reduce the number of comparisons if the list is already sorted – leaving one with a best case and worst case scenario for comparisons. Likewise different approaches have different levels of item movement. Depending on what is more expensive, one may give priority to one approach compared to another based on what is more expensive, a comparison or a item move. Insertion Sort Insertion sort tries to reduce the number of key comparisons it performs compared to selection sort by not “doing anything” if things are sorted. Assume you had an collection of numbers in the following order… 10 18 25 30 23 17 45 35 There are 8 elements in the list. If we were to start at the front of the list – 10 18 25 & 30 are already sorted. Element 5 (23) however is smaller than element 4 (30) and so needs to be repositioned. We do this by copying the value at element 5 to a temporary holder, and then begin shifting the elements before it up one. So… Element 5 would be copied to a temporary holder 10 18 25 30 23 17 45 35 – T 23 Element 4 would shift to Element 5 10 18 25 30 30 17 45 35 – T 23 Element 3 would shift to Element 4 10 18 25 25 30 17 45 35 – T 23 Element 2 (18) is smaller than the temporary holder so we put the temporary holder value into Element 3. 10 18 23 25 30 17 45 35 – T 23   We now have a sorted list up to element 6. And so we would repeat the same process by moving element 6 to a temporary value and then shifting everything up by one from element 2 to element 5. As you can see, one major setback for this technique is the shifting values up one – this is because up to now we have been considering the collection to be an array. If however the collection was a linked list, we would not need to shift values up, but merely remove the link from the unsorted value and “reinsert” it in a sorted position. Which would reduce the number of transactions performed on the collection. So.. Insertion sort seems to perform better than selection sort – however an implementation is slightly more complicated. This is typical with most sorting algorithms – generally, greater performance leads to greater complexity. Also, insertion sort performs better if a collection of data is already sorted. If for instance you were handed a sorted collection of size n, then only n number of comparisons would need to be performed to verify that it is sorted. It’s important to note that insertion sort (array based) performs a number item moves – every time an item is “out of place” several items before it get shifted up. Shellsort – Diminishing Increment Sort So up to now we have covered Selection Sort & Insertion Sort. Selection Sort makes many comparisons and insertion sort (with an array) has the potential of making many item movements. Shellsort is an approach that takes the normal insertion sort and tries to reduce the number of item movements. In Shellsort, elements in a collection are viewed as sub-collections of a particular size. Each sub-collection is sorted so that the elements that are far apart move closer to their final position. Suppose we had a collection of 15 elements… 10 20 15 45 36 48 7 60 18 50 2 19 43 30 55 First we may view the collection as 7 sub-collections and sort each sublist, lets say at intervals of 7 10 60 55 – 20 18 – 15 50 – 45 2 – 36 19 – 48 43 – 7 30 10 55 60 – 18 20 – 15 50 – 2 45 – 19 36 – 43 48 – 7 30 (Sorted) We then sort each sublist at a smaller inter – lets say 4 10 55 60 18 – 20 15 50 2 – 45 19 36 43 – 48 7 30 10 18 55 60 – 2 15 20 50 – 19 36 43 45 – 7 30 48 (Sorted) We then sort elements at a distance of 1 (i.e. we apply a normal insertion sort) 10 18 55 60 2 15 20 50 19 36 43 45 7 30 48 2 7 10 15 18 19 20 30 36 43 45 48 50 55 (Sorted) The important thing with shellsort is deciding on the increment sequence of each sub-collection. From what I can tell, there isn’t any definitive method and depending on the order of your elements, different increment sequences may perform better than others. There are however certain increment sequences that you may want to avoid. An even based increment sequence (e.g. 2 4 8 16 32 …) should typically be avoided because it does not allow for even elements to be compared with odd elements until the final sort phase – which in a way would negate many of the benefits of using sub-collections. The performance on the number of comparisons and item movements of Shellsort is hard to determine, however it is considered to be considerably better than the normal insertion sort. Quicksort Quicksort uses a divide and conquer approach to sort a collection of items. The collection is divided into two sub-collections – and the two sub-collections are sorted and combined into one list in such a way that the combined list is sorted. The algorithm is in general pseudo code below… Divide the collection into two sub-collections Quicksort the lower sub-collection Quicksort the upper sub-collection Combine the lower & upper sub-collection together As hinted at above, quicksort uses recursion in its implementation. The real trick with quicksort is to get the lower and upper sub-collections to be of equal size. The size of a sub-collection is determined by what value the pivot is. Once a pivot is determined, one would partition to sub-collections and then repeat the process on each sub collection until you reach the base case. With quicksort, the work is done when dividing the sub-collections into lower & upper collections. The actual combining of the lower & upper sub-collections at the end is relatively simple since every element in the lower sub-collection is smaller than the smallest element in the upper sub-collection. Mergesort With quicksort, the average-case complexity was O(nlog2n) however the worst case complexity was still O(N*N). Mergesort improves on quicksort by always having a complexity of O(nlog2n) regardless of the best or worst case. So how does it do this? Mergesort makes use of the divide and conquer approach to partition a collection into two sub-collections. It then sorts each sub-collection and combines the sorted sub-collections into one sorted collection. The general algorithm for mergesort is as follows… Divide the collection into two sub-collections Mergesort the first sub-collection Mergesort the second sub-collection Merge the first sub-collection and the second sub-collection As you can see.. it still pretty much looks like quicksort – so lets see where it differs… Firstly, mergesort differs from quicksort in how it partitions the sub-collections. Instead of having a pivot – merge sort partitions each sub-collection based on size so that the first and second sub-collection of relatively the same size. This dividing keeps getting repeated until the sub-collections are the size of a single element. If a sub-collection is one element in size – it is now sorted! So the trick is how do we put all these sub-collections together so that they maintain their sorted order. Sorted sub-collections are merged into a sorted collection by comparing the elements of the sub-collection and then adjusting the sorted collection. Lets have a look at a few examples… Assume 2 sub-collections with 1 element each 10 & 20 Compare the first element of the first sub-collection with the first element of the second sub-collection. Take the smallest of the two and place it as the first element in the sorted collection. In this scenario 10 is smaller than 20 so 10 is taken from sub-collection 1 leaving that sub-collection empty, which means by default the next smallest element is in sub-collection 2 (20). So the sorted collection would be 10 20 Lets assume 2 sub-collections with 2 elements each 10 20 & 15 19 So… again we would Compare 10 with 15 – 10 is the winner so we add it to our sorted collection (10) leaving us with 20 & 15 19 Compare 20 with 15 – 15 is the winner so we add it to our sorted collection (10 15) leaving us with 20 & 19 Compare 20 with 19 – 19 is the winner so we add it to our sorted collection (10 15 19) leaving us with 20 & _ 20 is by default the winner so our sorted collection is 10 15 19 20. Make sense? Heapsort (still needs to be completed) So by now I am tired of sorting algorithms and trying to remember why they were so important. I think every year I go through this stuff I wonder to myself why are we made to learn about selection sort and insertion sort if they are so bad – why didn’t we just skip to Mergesort & Quicksort. I guess the only explanation I have for this is that sometimes you learn things so that you can implement them in future – and other times you learn things so that you know it isn’t the best way of implementing things and that you don’t need to implement it in future. Anyhow… luckily this is going to be the last one of my sorts for today. The first step in heapsort is to convert a collection of data into a heap. After the data is converted into a heap, sorting begins… So what is the definition of a heap? If we have to convert a collection of data into a heap, how do we know when it is a heap and when it is not? The definition of a heap is as follows: A heap is a list in which each element contains a key, such that the key in the element at position k in the list is at least as large as the key in the element at position 2k +1 (if it exists) and 2k + 2 (if it exists). Does that make sense? At first glance I’m thinking what the heck??? But then after re-reading my notes I see that we are doing something different – up to now we have really looked at data as an array or sequential collection of data that we need to sort – a heap represents data in a slightly different way – although the data is stored in a sequential collection, for a sequential collection of data to be in a valid heap – it is “semi sorted”. Let me try and explain a bit further with an example… Example 1 of Potential Heap Data Assume we had a collection of numbers as follows 1[1] 2[2] 3[3] 4[4] 5[5] 6[6] For this to be a valid heap element with value of 1 at position [1] needs to be greater or equal to the element at position [3] (2k +1) and position [4] (2k +2). So in the above example, the collection of numbers is not in a valid heap. Example 2 of Potential Heap Data Lets look at another collection of numbers as follows 6[1] 5[2] 4[3] 3[4] 2[5] 1[6] Is this a valid heap? Well… element with the value 6 at position 1 must be greater or equal to the element at position [3] and position [4]. Is 6 > 4 and 6 > 3? Yes it is. Lets look at element 5 as position 2. It must be greater than the values at [4] & [5]. Is 5 > 3 and 5 > 2? Yes it is. If you continued to examine this second collection of data you would find that it is in a valid heap based on the definition of a heap.

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  • MD3200 - 3 to 4x less throughput than MD1220. Am I missing something here?

    - by Igor Polishchuk
    I have two R710 servers with similar configuration. One in my office has MD1220 attached. Another one in the datacenter of my hosting services vendor has MD3200. I'm getting significantly worse throughput from MD3200 at my vendors setup. I'm mostly interested in sequential writes, and I'm getting these results in bonnie++ and dd tests: Seq. writes on MD1220 in my office: 1.1 GB/s - bonnie++, 1.3GB/s - dd Seq. writes on MD3200 at my vendor's: 240MB/s - bonnie++, 310MB/s - dd Unfortunately, I could not test the exactly the same configurations, but the two I have should be comparable. If anything, my good performing environment is cheaper than the bad performing. I expect at least similar throughput from these two setups. My vendor cannot really help me. Hopefully, somebody more familiar with the DAS performance can look at it and tell if I'm missing something here and my expectations are too high. To summarize, the question here is it reasonable to expect about 100MB/s of sequential write throughput per each couple of drives in RAID10 on MD3200? Is there any trick to enable such performance in MD3200 with dual controller as opposed to simple MD1220 with a single H800 adapter? More details about the configurations: A good one in my office: Dell R710 2CPU X5650 @ 2.67GHz 12 cores 96GB DDR3, OS: RHEL 5.5, kernel 2.6.18-194.26.1.el5 x86_64 20x300GB 2.5" SAS 10K in a single RAID10 1MB chunk size on MD1220 + Dell H800 I/O controller with 1GB cache in the host Not so good one at my vendor's: Dell R710 2CPU L5520 @ 2.27GHz 8 cores 144GB DDR3, OS: RHEL 5.5, kernel 2.6.18-194.11.4.el5 x86_64 20x146GB 2.5" SAS 15K in a single RAID10 512KB chunk size, Dell MD3200, 2 I/O controllers in array with 1GB cache each Additional information. I've also ran the same tests on the same vendor's host, but the storage was: two raids of 14x146GB 15K RPM drives RAID 10, striped together on the OS level on MD3000+MD1000. The performance was about 25% worse than on MD3200 despite having more drives. When I ran similar tests on the internal storage of my vendor's host (2x146GB 15K RPM drives RAID1, Perc 6i) I've got about 128MB/s seq. writes. Just two internal drives gave me about a half of 20 drives' throughput on MD3200. The random I/O performance of the MD3200 setup is ok, it gives me at least 1300 IOPS. I'm mostly have problems with sequentioal I/O throughput. Thank you for looking into it. Regards Igor

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  • RAID options for a LAMP web server

    - by jetboy
    I'm due to set up a LAMP web server with four drives and a RAID controller to act as a web server. The drives are 146Gb SAS, and the machine has two quad core processors and 16Gb RAM. There will be very few write operations to the MySQL database, and I'll be using as much caching as possible to reduce disk I/O. Question is: Would I be better off splitting the drives into two RAID 1 arrays, splitting up sequential and random disk I/O, or would I get better overall performance putting them all in a single RAID 1+0 array?

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  • centos iptables, restrict tcp port to specific ips

    - by user788171
    I would like to modify the iptables on my CentOS 5.8 server so that only specific ips can connect to the machine on a specific port. Currently, I have the following in my iptables file: -A RH-Firewall-1-INPUT -m state --state NEW -m tcp -p tcp --dport 5000 -j ACCEPT How would I modify that line if I wanted to allow access for only ips 1.1.1.1 and 1.1.1.2 for instance? (they might not necessarily be sequential ips when I do this for reals).

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  • Ubuntu bash command

    - by pedro
    List in long form files in the directory "/ etc" for the file "ETCDIR" and view them, while the monitor sequential manner. how i can do it? with commands tee and more

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  • Deleting huge chunks of data from mysql innodb

    - by mingyeow
    I need to delete a huge chunk of my data in my production database, which runs about 100GB in size. If possible, i would like to minimize my downtime. My selection criteria for deleting is likely to be DELETE * FROM POSTING WHERE USER.ID=5 AND UPDATED_AT<100 What is the best way to delete it? Build an index? Write a sequential script that deletes via paginating through the rows 1000 at a time?

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  • Printing barcode labels

    - by BoundforPNG
    I am trying to print barcodes for a library. I have generated a list of sequential numbers and copied them into Word 2003. I want Library name, barcode font, barcode number printed in an Avery 5160 label sheet. I can get it to work by going to tools, letters and mailing, Envelopes and Labels, labels tab and type in what data I want. I don't see how I can pull this data from the list in the word document rather than just what I type.

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  • bluetooth connection using pybluez

    - by srj0408
    I am working on bluetooth not exactly on bluetooth stack-development but to use bluetooth in one of my project. I had done all that before using some of the py-bluez commands like hciconfig, hcitool scan , then simple-agents and using serial module inside python. But that was quite random. We were able to connect only one specific device based on its bluetooth address and there was no facility of reconnection once the devices are disconnected. Now i want to try out this stuff in a sequential manner like this (i am doing that all on a RPI and for at present on ubuntu 12.04.) i) Store some names in a file along with some other information with respect to that device. ii) Run a script to find out the device in locality with those names and if any one if found, report that. For this step, i had taken a reference from BTBook , made available from MIT. Below is the script for the same, but that script only search for the single name. from bluetooth import * target_name = "XT1033" target_address = None nearby_devices = discover_devices() for address in nearby_devices: if target_name == lookup_name( address ): target_address = address break if target_address is not None: print "found target bluetooth device with address ", target_address connect_socket(target_address); else: print "could not find target bluetooth device nearby" iii) Connect the device using client sock. But i dont have any device on which i can write a simple python script. My client can be any device that will be publishing data. Now i came through a script in the same book, that actually connect to a client requesting permission to connect to server. from bluetooth import * port = 1 server_sock=BluetoothSocket( RFCOMM ) server_sock.bind(("",port)) server_sock.listen(1) client_sock, client_info = server_sock.accept() print "Accepted connection from ", client_info data = client_sock.recv(1024) print "received [%s]" % data client_sock.close() server_sock.close() here client_sock, client_info = server_sock.accept() provide the client address and port requested to be connected. Can i pass address obtained from the earlier script to this, so that it connect server to the client? iv) Then if client get disconnected, re-connect(a simple polling can be used.) All this stuff can be done using bash and py-bluez functions but i want to do that in a sequential manner.I am not a master in python but i can do some small stuff. Can any one guide me for the same or can direct me to more usefull resource through which i can continue my coding part after finding the "X", "Y" named devices.

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  • Linked List is now Patented?

    - by John Isaiah Carmona
    Linked list Ming-Jen Wang Patent number: 7028023 Filing date: Sep 26, 2002 Issue date: Apr 11, 2006 Application number: 10/260,471 A computerized list is provided with auxiliary pointers for traversing the list in different sequences. One or more auxiliary pointers enable a fast, sequential traversal of the list with a minimum of computational time. Such lists may be used in any application where lists may be reordered for various purposes. Does this mean that I need to acquire permission before using a linked list in my codes? What about the codes I write from my previous apps that uses a linked list? What about the framework that implements the linked list?

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  • synchronization web service methodologies or papers

    - by Grady Player
    I am building a web service (PHP+JSON) to sync with my iphone app. The main goals are: Backup Provide a web view for printing / sorting, manipulating. allow a group sync up and down. I am aware of the logic problems with all of these items, Ie. if one person deletes something, do you persist this change to other users, collisions, etc. I am looking for just any book or scholarly work, or even words of wisdom to address common issues. when to detect changes of data with hashes, vs modified dates, or combination. how do address consolidation of sequential ID's originating on different client nodes (can be sidestepped in my context, but it would be interesting.) dealing with collisions (is there a universally safe way to do so?). general best practices. how to structure the actual data transaction (ask for whole list then detect changes...)

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  • structure problem in Relational DBMS creation

    - by Kane
    For learning and understanding purpose, I currently want to try to make a small relational DBMS with simple features like (for now) only sequential reading/writing and CREATE TABLE, INSERT, SELECT, UPDATE and DELETE management. I am currently on the "think" part of the project and I am stuck on the way to store the read data in memory. First I was thinking of putting them properly on a structure, but the problem is that tables are all different, know the type of each column is not an issue, but I am not sure C provide a way to make fully dynamic structure. My second and current idea is to make a simple char array of the required length and just get the data by order with cast. But I am not sure if it is the good way to do that part, so I wanted to ask for your opinion and advices about that. Thanks in advance for your help. nb: I hope my question is enough clear and understandable, I still lack of pratice in english

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  • PDF or ebook Java API documentation

    - by AmaDaden
    Since I have a long train ride to and from work I was wondering if there is a version of the Java API documentation floating around that I could put on my Kindle. It would be nice on the rare occasion I get something in my head that I want to think about some more. I know I can browse the web through the Kindle but coverage is spotty and slow. I know that the api docs are not really designed for a sequential reading format but I'm curious to see if anyone else has thought about this and given it a shot.

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  • Possibility of recovering files from a dd zero-filled hard disk

    - by unknownthreat
    I have "zero filled" (complete wiped) an external hard disk using dd, and from what I have heard: people said you should at least "zero fill" 3 times to be sure that the data are really wiped and no one can recover anything. So I decided to scan the disk once again after I've zero filled the disk. I was expecting the disk to still have some random binary left. It turned out that it has only a few sequential bytes in the very beginning. This is probably the file structure type and other headers stuff. Other than that, it's all zeros and nothing else. So if we have to recover any file from a zero filled disk, ...how? From what I've heard, even you zero fill the disk, you should still have some data left. ...or could dd really completely annihilate all data?

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