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  • Set a session hash outside of RoR program?

    - by Sindri Guðmundsson
    Hi, I have had my new rails program up for a few days now. I'm running it on Ubuntu 10.4 with apache2 in another location than the website it's made for (it's a standalone database application for physiotherapists). The people I made it for now want me to deploy it to the public part of their website, only with one change. Those who open it via the link in the public-part should not be able to click one button! I was thinking of doing something like this in my view: <% if session[:inside]%> <%=button_to 'Sækja mælitæki', @link_to_mt%> <%end%> How could I set session[:inside] only to true if the program was started from within the private part of the webpage? I thought of creating two new actions, the other would set session[:inside] to true and the other to false, but that seems to me like a security risk, is it not? BR, Sindri

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  • How do I quiet image_submit_tag from params hash?

    - by Alan S
    Does anyone know how to eliminate the x and y params when you use image_submit_tag with a get method? I have a simple search form, and using get to pass the value in the url. When I use image_submit_tag, it also appends the x and y coords, so I get urls like http://example.com?q=somesearchterm&x=15&y=12 When I have used submit_tag, I can use the :name = nil attribute (was in one of Ryan Bates' Railscasts), but it doesn't seem to work for image_submit_tag. Granted it doesn't affect functionality, but I don't need them and would like them quieted.

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  • Birthday effect - clarification needed plz.

    - by Mark
    Please help interpret the Birthday effect as described in Wikipedia: A birthday attack works as follows: 1) Pick any message m and compute h(m). 2) Update list L. Check if h(m) is in the list L. 3) if (h(m),m) is already in L, a colliding message pair has been found. else save the pair (h(m),m) in the list L and go back to step 1. From the birthday paradox we know that we can expect to find a matching entry, after performing about 2^(n/2) hash evaluations. Does the above mean 2^(n/2) iterations through the above entire loop (i.e. 2^(n/2) returns to step 1), OR does it mean 2^(n/2) comparisons to individual items already in L.

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  • What hash/map based programming language exist?

    - by Davorak
    Much like lisp is often considered a list based programming language what languages are considered map based? I remember reading about one a few years back, but can not longer find a reference to it. It looked something like: [if:test then:<code> else:<more code>] edit: and more where quoted code blocks which would be conditional evaluated. In this fashion if/cond and others would not be special form as they are in lisp/scheme.

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  • Can someone please clarify the Birthday Effect for me?

    - by Mark
    Please help interpret the Birthday effect as described in Wikipedia: A birthday attack works as follows: Pick any message m and compute h(m). Update list L. Check if h(m) is in the list L. if (h(m),m) is already in L, a colliding message pair has been found. else save the pair (h(m),m) in the list L and go back to step 1. From the birthday paradox we know that we can expect to find a matching entry, after performing about 2^(n/2) hash evaluations. Does the above mean 2^(n/2) iterations through the above entire loop (i.e. 2^(n/2) returns to step 1), OR does it mean 2^(n/2) comparisons to individual items already in L.

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  • Union of two or more (hash)maps

    - by javierfp
    I have two Maps that contain the same type of Objects: Map<String, TaskJSO> a = new HashMap<String, TaskJSO>(); Map<String, TaskJSO> b = new HashMap<String, TaskJSO>(); public class TaskJSO { String id; } The map keys are the "id" properties. a.put(taskJSO.getId(), taskJSO); I want to obtain a list with: all values in "Map b" + all values in "Map a" that are not in "Map b". What is the fastest way of doing this operation? Thanks EDIT: The comparaison is done by id. So, two TaskJSOs are considered as equal if they have the same id (equals method is overrided). My intention is to know which is the fastest way of doing this operation from a performance point of view. For instance, is there any difference if I do the "comparaison" in a map (as suggested by Peter): Map<String, TaskJSO> ab = new HashMap<String, TaskJSO>(a); ab.putAll(b); ab.values() or if instead I use a set (as suggested by Nishant): Set s = new Hashset(); s.addAll(a.values()); s.addAll(b.values());

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  • When should I define an hash code function for my types?

    - by devoured elysium
    Is there any other reason for implementing an hash code function for my types other than allowing for good use of hash tables? Let's say I am designing some types that I intend to use internally. I know that types are "internal" to the system, and I also know I will never use those types in hash tables. In spite of this, I decide I will have to redefine the equals() method. Theory says I should also redefine the hash code method, but I can't see any reason why, in this case, I should do it. Can anyone point me out any other reason? This question can be rephrased to : in which situations should we implement a hash code method in our types. PS : I am not asking how to implement one. I am asking when.

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  • How can I determine if a given git hash exists on a given branch?

    - by pinko
    Background: I use an automated build system which takes a git hash as input, as well as the name of the branch on which that hash exists, and builds it. However, the build system uses the hash alone to check out the code and build it -- it simply stores the branch name, as given, in the build DB metadata. I'm worried about developers accidentally providing the wrong branch name when they kick off a build, causing confusion when people are looking through the build history. So how can I confirm, before passing along the hash and branch name to the build system, that the given hash does in fact come from the given branch?

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  • What would a compress method do in a hash table?

    - by Bradley Oesch
    For an assignment I have to write the code for a generic Hash Table. In an example Put method, there are two lines: int hash = key.hashCode(); // get the hashcode of the key int index = compress(hash); // compress it to an index I was of the understanding that the hashCode method used the key to return an index, and you would place the key/value pair in the array at that index. But here we "compress" the hash code to get the index. What does this method do? How does it "compress" the hash code? Is it necessary and/or preferred?

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  • JBoss Clustered Service that sends emails from txt file

    - by michael lucas
    I need a little push in the right direction. Here's my problem: I have to create an ultra-reliable service that sends email messages to clients whose addresses are stored in txt file on FTP server. Single txt file may contain unlimited number of entries. Most often the file contains about 300,000 entries. Service exposes interface with just two simple methods: TaskHandle sendEmails(String ftpFilePath); ProcessStatus checkProcessStatus(TaskHandle taskHandle); Method sendEmails() returns TaskHandle by which we can ask for ProcessStatus. For such a service to be reliable clustering is necessary. Processing single txt file might take a long time. Restarting one node in a cluster should have no impact on sending emails. We use JBoss AS 4.2.0 which comes with a nice HASingletonController that ensure one instance of service is running at given time. But once a fail-over happens, the second service should continue work from where the first one stopped. How can I share state between nodes in a cluster in such a way that leaves no possibility of sending some emails twice?

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  • Collision Attacks, Message Digests and a Possible solution

    - by Dominar
    I've been doing some preliminary research in the area of message digests. Specifically collision attacks of cryptographic hash functions such as MD5 and SHA-1, such as the Postscript example and X.509 certificate duplicate. From what I can tell in the case of the postscript attack, specific data was generated and embedded within the header of the postscript (which is ignored during rendering) which brought about the internal state of the md5 to a state such that the modified wording of the document would lead to a final MD equivalent to the original. The X.509 took a similar approach where by data was injected within the comment/whitespace of the certificate. Ok so here is my question, and I can't seem to find anyone asking this question: Why isn't the length of ONLY the data being consumed added as a final block to the MD calculation? In the case of X.509 - Why is the whitespace and comments being taken into account as part of the MD? Wouldn't a simple processes such as one of the following be enough to resolve the proposed collision attacks: MD(M + |M|) = xyz MD(M + |M| + |M| * magicseed_0 +...+ |M| * magicseed_n) = xyz where : M : is the message |M| : size of the message MD : is the message digest function (eg: md5, sha, whirlpool etc) xyz : is the acutal message digest value for the message M magicseed_{i}: Is a set random values generated with seed based on the internal-state prior to the size being added. This technqiue should work, as to date all such collision attacks rely on adding more data to the original message. In short, the level of difficulty involved in generating a collision message such that: It not only generates the same MD But is also comprehensible/parsible/compliant and is also the same size as the original message, is immensely difficult if not near impossible. Has this approach ever been discussed? Any links to papers etc would be nice.

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  • What is the difference between using MD5.Create and MD5CryptoServiceProvider?

    - by byte
    In the .NET framework there are a couple of ways to calculate an MD5 hash it seems, however there is something I don't understand; What is the distinction between the following? What sets them apart from eachother? They seem to product identical results: public static string GetMD5Hash(string str) { MD5CryptoServiceProvider md5 = new MD5CryptoServiceProvider(); byte[] bytes = ASCIIEncoding.Default.GetBytes(str); byte[] encoded = md5.ComputeHash(bytes); StringBuilder sb = new StringBuilder(); for (int i = 0; i < encoded.Length; i++) sb.Append(encoded[i].ToString("x2")); return sb.ToString(); } public static string GetMD5Hash2(string str) { System.Security.Cryptography.MD5 md5 = System.Security.Cryptography.MD5.Create(); byte[] bytes = Encoding.Default.GetBytes(str); byte[] encoded = md5.ComputeHash(bytes); StringBuilder sb = new StringBuilder(); for (int i = 0; i < encoded.Length; i++) sb.Append(encoded[i].ToString("x2")); return sb.ToString(); }

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  • Writing a JavaScript zip code validation function

    - by mkoryak
    I would like to write a JavaScript function that validates a zip code, by checking if the zip code actually exists. Here is a list of all zip codes: http://www.census.gov/tiger/tms/gazetteer/zips.txt (I only care about the 2nd column) This is really a compression problem. I would like to do this for fun. OK, now that's out of the way, here is a list of optimizations over a straight hashtable that I can think of, feel free to add anything I have not thought of: Break zipcode into 2 parts, first 2 digits and last 3 digits. Make a giant if-else statement first checking the first 2 digits, then checking ranges within the last 3 digits. Or, covert the zips into hex, and see if I can do the same thing using smaller groups. Find out if within the range of all valid zip codes there are more valid zip codes vs invalid zip codes. Write the above code targeting the smaller group. Break up the hash into separate files, and load them via Ajax as user types in the zipcode. So perhaps break into 2 parts, first for first 2 digits, second for last 3. Lastly, I plan to generate the JavaScript files using another program, not by hand. Edit: performance matters here. I do want to use this, if it doesn't suck. Performance of the JavaScript code execution + download time. Edit 2: JavaScript only solutions please. I don't have access to the application server, plus, that would make this into a whole other problem =)

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  • (Rails) Creating multi-dimensional hashes/arrays from a data set...?

    - by humble_coder
    Hi All, I'm having a bit of an issue wrapping my head around something. I'm currently using a hacked version of Gruff in order to accommodate "Scatter Plots". That said, the data is entered in the form of: g.data("Person1",[12,32,34,55,23],[323,43,23,43,22]) ...where the first item is the ENTITY, the second item is X-COORDs, and the third item is Y-COORDs. I currently have a recordset of items from a table with the columns: POINT, VALUE, TIMESTAMP. Due to the "complex" calculations involved I must grab everything using a single query or risk way too much DB activity. That said, I have a list of items for which I need to dynamically collect all data from the recordset into a hash (or array of arrays) for the creation of the data items. I was thinking something like the following: @h={} e = Events.find_by_sql(my_query) e.each do |event| @h["#{event.Point}"][x] = event.timestamp @h["#{event.Point}"][y] = event.value end Obviously that's not the correct syntax, but that's where my brain is going. Could someone clean this up for me or suggest a more appropriate mechanism by which to accomplish this? Basically the main goal is to keep data for each pointname grouped (but remember the recordset has them all). Much appreciated. EDIT 1 g = Gruff::Scatter.new("600x350") g.title = self.name e = Event.find_by_sql(@sql) h ={} e.each do |event| h[event.Point.to_s] ||= {} h[event.Point.to_s].merge!({event.Timestamp.to_i,event.Value}) end h.each do |p| logger.info p[1].values.inspect g.data(p[0],p[1].keys,p[1].values) end g.write(@chart_file)

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  • Hashing 11 byte unique ID to 32 bits or less

    - by MoJo
    I am looking for a way to reduce a 11 byte unique ID to 32 bits or fewer. I am using an Atmel AVR microcontroller that has the ID number burned in at the factory, but because it has to be transmitted very often in a very low power system I want to reduce the length down to 4 bytes or fewer. The ID is guaranteed unique for every microcontroller. It is made up of data from the manufacturing process, basically the coordinates of the silicone on the wafer and the production line that was used. They look like this: 304A34393334-16-11001000 314832383431-0F-09000C00 Obviously the main danger is that by reducing these IDs they become non-unique. Unfortunately I don't have a large enough sample size to test how unique these numbers are. Having said that because there will only be tens of thousands of devices in use and there is secondary information that can be used to help identify them (such as their approximate location, known at the time of communication) collisions might not be too much of an issue if they are few and far between. Is something like MD5 suitable for this? My concern is that the data being hashed is very short, just 11 bytes. Do hash functions work reliably on such short data?

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  • Why can't we just use a hash of passphrase as the encryption key (and IV) with symmetric encryption algorithms?

    - by TX_
    Inspired by my previous question, now I have a very interesting idea: Do you really ever need to use Rfc2898DeriveBytes or similar classes to "securely derive" the encryption key and initialization vector from the passphrase string, or will just a simple hash of that string work equally well as a key/IV, when encrypting the data with symmetric algorithm (e.g. AES, DES, etc.)? I see tons of AES encryption code snippets, where Rfc2898DeriveBytes class is used to derive the encryption key and initialization vector (IV) from the password string. It is assumed that one should use a random salt and a shitload of iterations to derive secure enough key/IV for the encryption. While deriving bytes from password string using this method is quite useful in some scenarios, I think that's not applicable when encrypting data with symmetric algorithms! Here is why: using salt makes sense when there is a possibility to build precalculated rainbow tables, and when attacker gets his hands on hash he looks up the original password as a result. But... with symmetric data encryption, I think this is not required, as the hash of password string, or the encryption key, is never stored anywhere. So, if we just get the SHA1 hash of password, and use it as the encryption key/IV, isn't that going to be equally secure? What is the purpose of using Rfc2898DeriveBytes class to generate key/IV from password string (which is a very very performance-intensive operation), when we could just use a SHA1 (or any other) hash of that password? Hash would result in random bit distribution in a key (as opposed to using string bytes directly). And attacker would have to brute-force the whole range of key (e.g. if key length is 256bit he would have to try 2^256 combinations) anyway. So either I'm wrong in a dangerous way, or all those samples of AES encryption (including many upvoted answers here at SO), etc. that use Rfc2898DeriveBytes method to generate encryption key and IV are just wrong.

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  • Is this the best way to grab common elements from a Hash of arrays?

    - by Hulihan Applications
    I'm trying to get a common element from a group of arrays in Ruby. Normally, you can use the & operator to compare two arrays, which returns elements that are present or common in both arrays. This is all good, except when you're trying to get common elements from more than two arrays. However, I want to get common elements from an unknown, dynamic number of arrays, which are stored in a hash. I had to resort to using the eval() method in ruby, which executes a string as actual code. Here's the function I wrote: def get_common_elements_for_hash_of_arrays(hash) # get an array of common elements contained in a hash of arrays, for every array in the hash. # ["1","2","3"] & ["2","4","5"] & ["2","5","6"] # => ["2"] # eval("[\"1\",\"2\",\"3\"] & [\"2\",\"4\",\"5\"] & [\"2\",\"5\",\"6\"]") # => ["2"] eval_string_array = Array.new # an array to store strings of Arrays, ie: "[\"2\",\"5\",\"6\"]", which we will join with & to get all common elements hash.each do |key, array| eval_string_array << array.inspect end eval_string = eval_string_array.join(" & ") # create eval string delimited with a & so we can get common values return eval(eval_string) end example_hash = {:item_0 => ["1","2","3"], :item_1 => ["2","4","5"], :item_2 => ["2","5","6"] } puts get_common_elements_for_hash_of_arrays(example_hash) # => 2 This works and is great, but I'm wondering...eval, really? Is this the best way to do it? Are there even any other ways to accomplish this(besides a recursive function, of course). If anyone has any suggestions, I'm all ears. Otherwise, Feel free to use this code if you need to grab a common item or element from a group or hash of arrays, this code can also easily be adapted to search an array of arrays.

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  • Is this the best way to grab Common element from a Hash of arrays?

    - by Hulihan Applications
    I'm trying to get a common element from a group of arrays in Ruby. Normally, you can use the & operator to compare two arrays, which returns elements that are present or common in both arrays. This is all good, except when you're trying to get common elements from more than two arrays. However, I want to get common elements from an unknown, dynamic number of arrays, which are stored in a hash. I had to resort to using the eval() method in ruby, which executes a string as actual code. Here's the function I wrote: def get_common_elements_for_hash_of_arrays(hash) # get an array of common elements contained in a hash of arrays, for every array in the hash. # ["1","2","3"] & ["2","4","5"] & ["2","5","6"] # => ["2"] # eval("[\"1\",\"2\",\"3\"] & [\"2\",\"4\",\"5\"] & [\"2\",\"5\",\"6\"]") # => ["2"] eval_string_array = Array.new # an array to store strings of Arrays, ie: "[\"2\",\"5\",\"6\"]", which we will join with & to get all common elements hash.each do |key, array| eval_string_array << array.inspect end eval_string = eval_string_array.join(" & ") # create eval string delimited with a & so we can get common values return eval(eval_string) end example_hash = {:item_0 => ["1","2","3"], :item_1 => ["2","4","5"], :item_2 => ["2","5","6"] } puts get_common_elements_for_hash_of_arrays(example_hash) # => 2 This works and is great, but I'm wondering...eval, really? Is this the best way to do it? Are there even any other ways to accomplish this(besides a recursive function, of course). If anyone has any suggestions, I'm all ears. Otherwise, Feel free to use this code if you need to grab a common item or element from a group or hash of arrays, this code can also easily be adapted to search an array of arrays.

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  • Boost MultiIndex - objects or pointers (and how to use them?)?

    - by Sarah
    I'm programming an agent-based simulation and have decided that Boost's MultiIndex is probably the most efficient container for my agents. I'm not a professional programmer, and my background is very spotty. I've two questions: Is it better to have the container contain the agents (of class Host) themselves, or is it more efficient for the container to hold Host *? Hosts will sometimes be deleted from memory (that's my plan, anyway... need to read up on new and delete). Hosts' private variables will get updated occasionally, which I hope to do through the modify function in MultiIndex. There will be no other copies of Hosts in the simulation, i.e., they will not be used in any other containers. If I use pointers to Hosts, how do I set up the key extraction properly? My code below doesn't compile. // main.cpp - ATTEMPTED POINTER VERSION ... #include <boost/multi_index_container.hpp> #include <boost/multi_index/hashed_index.hpp> #include <boost/multi_index/member.hpp> #include <boost/multi_index/ordered_index.hpp> #include <boost/multi_index/mem_fun.hpp> #include <boost/tokenizer.hpp> typedef multi_index_container< Host *, indexed_by< // hash by Host::id hashed_unique< BOOST_MULTI_INDEX_MEM_FUN(Host,int,Host::getID) > // arg errors here > // end indexed_by > HostContainer; ... int main() { ... HostContainer testHosts; Host * newHostPtr; newHostPtr = new Host( t, DOB, idCtr, 0, currentEvents ); testHosts.insert( newHostPtr ); ... } I can't find a precisely analogous example in the Boost documentation, and my knowledge of C++ syntax is still very weak. The code does appear to work when I replace all the pointer references with the class objects themselves. As best I can read it, the Boost documentation (see summary table at bottom) implies I should be able to use member functions with pointer elements.

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  • How to Achieve OC4J RMI Load Balancing

    - by fip
    This is an old, Oracle SOA and OC4J 10G topic. In fact this is not even a SOA topic per se. Questions of RMI load balancing arise when you developed custom web applications accessing human tasks running off a remote SOA 10G cluster. Having returned from a customer who faced challenges with OC4J RMI load balancing, I felt there is still some confusions in the field how OC4J RMI load balancing work. Hence I decide to dust off an old tech note that I wrote a few years back and share it with the general public. Here is the tech note: Overview A typical use case in Oracle SOA is that you are building web based, custom human tasks UI that will interact with the task services housed in a remote BPEL 10G cluster. Or, in a more generic way, you are just building a web based application in Java that needs to interact with the EJBs in a remote OC4J cluster. In either case, you are talking to an OC4J cluster as RMI client. Then immediately you must ask yourself the following questions: 1. How do I make sure that the web application, as an RMI client, even distribute its load against all the nodes in the remote OC4J cluster? 2. How do I make sure that the web application, as an RMI client, is resilient to the node failures in the remote OC4J cluster, so that in the unlikely case when one of the remote OC4J nodes fail, my web application will continue to function? That is the topic of how to achieve load balancing with OC4J RMI client. Solutions You need to configure and code RMI load balancing in two places: 1. Provider URL can be specified with a comma separated list of URLs, so that the initial lookup will land to one of the available URLs. 2. Choose a proper value for the oracle.j2ee.rmi.loadBalance property, which, along side with the PROVIDER_URL property, is one of the JNDI properties passed to the JNDI lookup.(http://docs.oracle.com/cd/B31017_01/web.1013/b28958/rmi.htm#BABDGFBI) More details below: About the PROVIDER_URL The JNDI property java.name.provider.url's job is, when the client looks up for a new context at the very first time in the client session, to provide a list of RMI context The value of the JNDI property java.name.provider.url goes by the format of a single URL, or a comma separate list of URLs. A single URL. For example: opmn:ormi://host1:6003:oc4j_instance1/appName1 A comma separated list of multiple URLs. For examples:  opmn:ormi://host1:6003:oc4j_instanc1/appName, opmn:ormi://host2:6003:oc4j_instance1/appName, opmn:ormi://host3:6003:oc4j_instance1/appName When the client looks up for a new Context the very first time in the client session, it sends a query against the OPMN referenced by the provider URL. The OPMN host and port specifies the destination of such query, and the OC4J instance name and appName are actually the “where clause” of the query. When the PROVIDER URL reference a single OPMN server Let's consider the case when the provider url only reference a single OPMN server of the destination cluster. In this case, that single OPMN server receives the query and returns a list of the qualified Contexts from all OC4Js within the cluster, even though there is a single OPMN server in the provider URL. A context represent a particular starting point at a particular server for subsequent object lookup. For example, if the URL is opmn:ormi://host1:6003:oc4j_instance1/appName, then, OPMN will return the following contexts: appName on oc4j_instance1 on host1 appName on oc4j_instance1 on host2, appName on oc4j_instance1 on host3,  (provided that host1, host2, host3 are all in the same cluster) Please note that One OPMN will be sufficient to find the list of all contexts from the entire cluster that satisfy the JNDI lookup query. You can do an experiment by shutting down appName on host1, and observe that OPMN on host1 will still be able to return you appname on host2 and appName on host3. When the PROVIDER URL reference a comma separated list of multiple OPMN servers When the JNDI propery java.naming.provider.url references a comma separated list of multiple URLs, the lookup will return the exact same things as with the single OPMN server: a list of qualified Contexts from the cluster. The purpose of having multiple OPMN servers is to provide high availability in the initial context creation, such that if OPMN at host1 is unavailable, client will try the lookup via OPMN on host2, and so on. After the initial lookup returns and cache a list of contexts, the JNDI URL(s) are no longer used in the same client session. That explains why removing the 3rd URL from the list of JNDI URLs will not stop the client from getting the EJB on the 3rd server. About the oracle.j2ee.rmi.loadBalance Property After the client acquires the list of contexts, it will cache it at the client side as “list of available RMI contexts”.  This list includes all the servers in the destination cluster. This list will stay in the cache until the client session (JVM) ends. The RMI load balancing against the destination cluster is happening at the client side, as the client is switching between the members of the list. Whether and how often the client will fresh the Context from the list of Context is based on the value of the  oracle.j2ee.rmi.loadBalance. The documentation at http://docs.oracle.com/cd/B31017_01/web.1013/b28958/rmi.htm#BABDGFBI list all the available values for the oracle.j2ee.rmi.loadBalance. Value Description client If specified, the client interacts with the OC4J process that was initially chosen at the first lookup for the entire conversation. context Used for a Web client (servlet or JSP) that will access EJBs in a clustered OC4J environment. If specified, a new Context object for a randomly-selected OC4J instance will be returned each time InitialContext() is invoked. lookup Used for a standalone client that will access EJBs in a clustered OC4J environment. If specified, a new Context object for a randomly-selected OC4J instance will be created each time the client calls Context.lookup(). Please note the regardless of the setting of oracle.j2ee.rmi.loadBalance property, the “refresh” only occurs at the client. The client can only choose from the "list of available context" that was returned and cached from the very first lookup. That is, the client will merely get a new Context object from the “list of available RMI contexts” from the cache at the client side. The client will NOT go to the OPMN server again to get the list. That also implies that if you are adding a node to the server cluster AFTER the client’s initial lookup, the client would not know it because neither the server nor the client will initiate a refresh of the “list of available servers” to reflect the new node. About High Availability (i.e. Resilience Against Node Failure of Remote OC4J Cluster) What we have discussed above is about load balancing. Let's also discuss high availability. This is how the High Availability works in RMI: when the client use the context but get an exception such as socket is closed, it knows that the server referenced by that Context is problematic and will try to get another unused Context from the “list of available contexts”. Again, this list is the list that was returned and cached at the very first lookup in the entire client session.

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  • Shrink NTFS Windows 7 Partition with GParted

    - by user15961
    I am running a dual-boot system with Windows 7 and Ubuntu 10.10. Initially I allocated about 20GB for my Ubuntu partition; however, I quickly ran out of that space and am now looking to expand my partition. Currently my NTFS partition (450GB) has about 130GB of free space. I tried using GParted to shrink the partition but encountered the following error. I booted into windows so I could run chkdsk but the countdown freezes at 1 upon reboot. I tried multiple methods to resolve that issue but nothing seems to work. Finally I gave up, and now I just want to know what is the best way for me to force GParted to shrink the partition regardless of the errors. I don't really have anything important and I don't mind risking the data. I just don't want to wipe the entire NTFS partition because I don't have a Windows install CD and might require Windows later on for some programs. I tried using sudo ntfsresize but that spews out the same error as GParted... Any ideas? Check and repair file system (ntfs) on /dev/sda2 00:00:09 ( ERROR ) calibrate /dev/sda2 00:00:00 ( SUCCESS ) path: /dev/sda2 start: 36944325 end: 976771119 size: 939826795 (448.14 GiB) check file system on /dev/sda2 for errors and (if possible) fix them 00:00:09 ( ERROR ) ntfsresize -P -i -f -v /dev/sda2 ntfsresize v2.0.0 (libntfs 10:0:0) Device name : /dev/sda2 NTFS volume version: 3.1 Cluster size : 4096 bytes Current volume size: 481191318016 bytes (481192 MB) Current device size: 481191319040 bytes (481192 MB) Checking for bad sectors ... Checking filesystem consistency ... Cluster 63468 is referenced multiple times! Cluster 63469 is referenced multiple times! Cluster 63465 is referenced multiple times! Cluster 63466 is referenced multiple times! Cluster 63467 is referenced multiple times! Cluster 165621 is referenced multiple times! Cluster 165622 is referenced multiple times! Cluster 165623 is referenced multiple times! Cluster 165624 is referenced multiple times! ERROR: Filesystem check failed! ERROR: 9 clusters are referenced multiply times. NTFS is inconsistent. Run chkdsk /f on Windows then reboot it TWICE! The usage of the /f parameter is very IMPORTANT! No modification was and will be made to NTFS by this software until it gets repaired.

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