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  • Cleaning up code - flatten a nested hash structure

    - by knorv
    The following Perl sub flattens a nested hash structure: sub flatten { my $hashref = shift; my %hash; my %i = %{$hashref}; foreach my $ii (keys(%i)) { my %j = %{$i{$ii}}; foreach my $jj (keys(%j)) { my %k = %{$j{$jj}}; foreach my $kk (keys(%k)) { my $value = $k{$kk}; $hash{$kk} = $value; } } } return %hash; } While the code works it is not very readable or clean. My question is two-fold: In what ways does it not correspond to modern Perl best practices? How would you clean it up?

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  • Combine hash values in C#

    - by Chris
    I'm creating a generic object collection class and need to implement a Hash function. I can obviously (and easily!) get the hash values for each object but was looking for the 'correct' way to combine them to avoid any issues. Does just adding, xoring or any basic operation harm the quality of the hash or am I going to have to do something like getting the objects as bytes, combining them and then hashing that? Cheers in advance

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  • Do I need to enable DRS to use Dynacache in Websphere Application Server Cluster

    - by rabs
    We are running a websphere commerce application with several websphere application servers configured in a cluster. We are using dynacache, so each server in the cluster will have its own cached objects in its own JVM. We are using CACHEIVL with database triggers for all cache invalidations. I was reading http://www.ibm.com/developerworks/websphere/library/techarticles/0603_crick/0603_crick.html and found an interesting sentence: "Furthermore, cache replication is necessary to ensure that invalidation messages are shared between the servers in a cluster." After thinking about this it would make sense that for the invalidation to work it would need to be triggered on all the servers in the cluster, but I couldn't find confirmation of this in the mountains of IBM doco. Does anyone know if you can use trigger based cache invalidation (through CACHEIVL) when you have several application servers clustered each with their own cache without DRS turned on? or do I need to use DRS for this to work?

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  • How can I marshal a hash with arrays?

    - by tuner
    What should I do to marshal an hash of arrays? The following code only prints {}. s = Hash.new s.default = Array.new s[0] << "Tigger" s[7] << "Ruth" s[7] << "Puuh" data = Marshal.dump(s) ls = Marshal.restore( data ) p ls If the hash doesn't contain an array it is restored properly.

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  • Hash value in the manifest file.

    - by satishtech
    Hello, Im tring to create a manifest for my own.dll, i took the manifest file from C:\WINDOWS\WinSxS\Manifests for example. In that, below tag was one of the line.<file name="msvcr90.dll" hashalg="SHA1" hash="e0dcdcbfcb452747da530fae6b000d47c8674671"> In above tag, hash value was assigned with 40 character. Here comes my doubt, 1) hash value was auto generated, if not, whats it points to?

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  • How do I access a value of a nested Perl hash?

    - by st
    I am new to Perl and I have a problem that's very simple but I cannot find the answer when consulting my Perl book. When printing the result of Dumper($request); I get the following result: $VAR1 = bless( { '_protocol' => 'HTTP/1.1', '_content' => '', '_uri' => bless( do{\(my $o = 'http://myawesomeserver.org:8081/counter/')}, 'URI::http' ), '_headers' => bless( { 'user-agent' => 'Mozilla/5.0 (X11; U; Linux i686; en; rv:1.9.0.4) Gecko/20080528 Epiphany/2.22 Firefox/3.0', 'connection' => 'keep-alive', 'cache-control' => 'max-age=0', 'keep-alive' => '300', 'accept' => 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 'accept-language' => 'en-us,en;q=0.5', 'accept-encoding' => 'gzip,deflate', 'host' => 'localhost:8081', 'accept-charset' => 'ISO-8859-1,utf-8;q=0.7,*;q=0.7' }, 'HTTP::Headers' ), '_method' => 'GET', '_handle' => bless( \*Symbol::GEN0, 'FileHandle' ) }, 'HTTP::Server::Simple::Dispatched::Request' ); How can I access the values of '_method' ('GET') or of 'host' ('localhost:8081'). I know that's an easy question, but Perl is somewhat cryptic at the beginning.

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  • Collision free hash function for a specific data structure

    - by Max
    Is it possible to create collision free hash function for a data structure with specific properties. The datastructure is int[][][] It contains no duplicates The range of integers that are contained in it is defined. Let's say it's 0..1000, the maximal integer is definitely not greater than 10000. Big problem is that this hash function should also be very fast. Is there a way to create such a hash function? Maybe at run time depending on the integer range?

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  • in ruby, how do you make this nested hash work?

    - by David
    this one creates an error: @settings = { :tab1 => { :name => { :required => true }, :description } } need to change :descrpition to :description = {}, but i don't have any values for :description so i want it to remain as is (without the empty = {}) Would you show me the best way to handle this kind of situation? thanks in advance

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  • How can I merge several hashes into one hash in Perl?

    - by Nick
    In Perl, how do I get this: $VAR1 = { '999' => { '998' => [ '908', '906', '0', '998', '907' ] } }; $VAR1 = { '999' => { '991' => [ '913', '920', '918', '998', '916', '919', '917', '915', '912', '914' ] } }; $VAR1 = { '999' => { '996' => [] } }; $VAR1 = { '999' => { '995' => [] } }; $VAR1 = { '999' => { '994' => [] } }; $VAR1 = { '999' => { '993' => [] } }; $VAR1 = { '999' => { '997' => [ '986', '987', '990', '984', '989', '988' ] } }; $VAR1 = { '995' => { '101' => [] } }; $VAR1 = { '995' => { '102' => [] } }; $VAR1 = { '995' => { '103' => [] } }; $VAR1 = { '995' => { '104' => [] } }; $VAR1 = { '995' => { '105' => [] } }; $VAR1 = { '995' => { '106' => [] } }; $VAR1 = { '995' => { '107' => [] } }; $VAR1 = { '994' => { '910' => [] } }; $VAR1 = { '993' => { '909' => [] } }; $VAR1 = { '993' => { '904' => [] } }; $VAR1 = { '994' => { '985' => [] } }; $VAR1 = { '994' => { '983' => [] } }; $VAR1 = { '993' => { '902' => [] } }; $VAR1 = { '999' => { '992' => [ '905' ] } }; to this: $VAR1 = { '999:' => [ { '992' => [ '905' ] }, { '993' => [ { '909' => [] }, { '904' => [] }, { '902' => [] } ] }, { '994' => [ { '910' => [] }, { '985' => [] }, { '983' => [] } ] }, { '995' => [ { '101' => [] }, { '102' => [] }, { '103' => [] }, { '104' => [] }, { '105' => [] }, { '106' => [] }, { '107' => [] } ] }, { '996' => [] }, { '997' => [ '986', '987', '990', '984', '989', '988' ] }, { '998' => [ '908', '906', '0', '998', '907' ] }, { '991' => [ '913', '920', '918', '998', '916', '919', '917', '915', '912', '914' ] } ]};

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  • Calculate sum of objects for each unique object property in Ruby

    - by macek
    I was helping with an answer in this question and it sparked a question of my own. Pie is an object that has a pieces array made of of PiePiece objects. Each PiePiece has a flavor attribute How do I create a hash that looks like this: # flavor => number of pieces { :cherry => 3 :apple => 1 :strawberry => 2 } This works, but I think it could be improved def inventory hash = {} pieces.each do |p| hash[p.flavor] ||= 0 hash[p.flavor] += 1 end hash end Any ideas?

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  • Using a Javascript Variable & Sending to JSON

    - by D Franks
    Hello all! I'm trying to take a URL's hash value, send it through a function, turn that value into an object, but ultimately send the value to JSON. I have the following setup: function content(cur){ var mycur = $H(cur); var pars = "p="+mycur.toJSON(); new Ajax.Updater('my_box', 'test.php', { parameters: pars }); } function update(){ if(window.location.hash.length > 0){ content(window.location.hash.substr(1)); // Everything after the '#' } } var curHashVal = window.location.hash; window.onload = function(){ setInterval(function(){ if(curHashVal != window.location.hash){ update(); curHashVal = window.location.hash; } },1); } But for some reason, I can't seem to get the right JSON output. It will either return as a very large object (1:"{",2:"k") or not return at all. I doubt that it is impossible to accomplish, but I've exhausted most of the ways I can think of. Other ways I've tried were "{" + cur + "}" as well as cur.toObject(), however, none seemed to get the job done. Thanks for the help!

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  • HPC Cluster planning workflow?

    - by Veronica
    After three days of intensive Google searching, I have not found any high-level workflow of how to build a low profile - cheap - computing cluster (we are not interested in HA yet). This is just a front-end plus a node for now. We want to start small with rockscluster, provide a web-based server for offering services, and then add nodes as our budget increases. We're small company, so we haven't enough human resources to implement it smoothly. Here are some facts about our environment: Our hardware is not constant (we will add nodes). Our workload will vary (in the order from 200Mb - 1Tb) Our software will change (scientific applications for data mining) Do you know any visual workflow, worksheet, chart, describing the general necessary steps to begin our cluster planning?

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  • Putting our OLTP and OLAP services on the same cluster

    - by Dynamo
    We're currently in a bit of a debate about what to do with our scattered SQL environment. We are setting up a cluster for our data warehouses for sure and are now in the process of deciding if our OLTP databases should go on the same one. The cluster will be active/active with database services running on one node and reporting and analytical services on the other node. From a technical standpoint I don't see an issue here. With the services being run on different nodes they shouldn't compete too heavily for resources. The only physical resource that may be an issue would be the shared disk space. Our environment is also quite small. Our biggest OLAP database at the moment is only about 40GB and our OLTP are all under 10GB. I see a potential political issue here as different groups are involved but I'm just strictly wondering if there would be any major technical issues that could arise from this setup.

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  • Hyper V cluster - one VM won't migrate

    - by Chris W
    We have a Failover Cluster built up on 6 blades, each running Hyper V. Each box is running Server 2008 R2. We've got a number of VMs running that all have the same basic config: VHD stored on a cluster shared volume. 2 virtual NICs (1 for LAN connection and 1 for SAN connection). All of our VMs will happily migrate between any other blade apart from one single VM which is running fine on it's current blade but will not migrate to any other location. What could be the cause of it or where should I look to get a detailed error message as I can't seem to find much information logged in any of the logs. Edit: I know the usual culprit is mis-matching resource names. We've already been there with the NICs named differently on some of the blades. As far as we can tell now everything looks to be identical on each bit of metal.

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  • Can i use a Windows 2008 r2 Cluster for file redundancy

    - by JERiv
    I'm researching a sever clustering architecture as a redundancy and backup solution for a client, and something that isn't made clear is whether or not i can use server clustering to replace a file server with backup solution. Forgive my Elementary understanding of server clustering but supposing: 2 Sites (NJ, CA) Identical Servers at each site setup as a Remote Site Cluster nodes with Windows Enterprise server 2008 r2 Services: File, Terminal, AD, and maybe DNS Will the following will be true: Files (including data drives) will be synced between the two servers eliminating the need for third party backup/mirroring software to sync/backup files. Also supposing i use roaming profiles w/ folder redirection; How will client computer in the WAN access their data through the cluster (i.e. will they automatically choose the best route)

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  • OCFS2 Now Certified for E-Business Suite Release 12 Application Tiers

    - by sergio.leunissen
    Steven Chan writes that OCFS2 is now certified for use as a clustered filesystem for sharing files between all of your E-Business Suite application tier servers.  OCFS2 (Oracle Cluster File System 2) is a free, open source, general-purpose, extent-based clustered file system which Oracle developed and contributed to the Linux community.  It was accepted into Linux kernel 2.6.16.OCFS2 is included in Oracle Enterprise Linux (OEL) and supported under Unbreakable Linux support.

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  • Focus On Systems Admins and Developers

    - by rickramsey
    Even if you're not going to Oracle Open World, you might find it interesting to hear what the different technology groups at Oracle are going to be talking about. And if you are going, here's your Systems schedule: Note: all links go to PDF files. Focus On: Oracle Linux Focus On: Oracle Solaris Focus On: Oracle Solaris Cluster Focus On: Oracle Solaris Studio Focus On: Desktop Virtualization Focus On: Oracle VM Server Virtualization Focus On: SPARC Servers Focus On: Storage Focus On: SPARC Supercluster - Rick Website Newsletter Facebook Twitter

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  • Developing Schema Compare for Oracle (Part 6): 9i Query Performance

    - by Simon Cooper
    All throughout the EAP and beta versions of Schema Compare for Oracle, our main request was support for Oracle 9i. After releasing version 1.0 with support for 10g and 11g, our next step was then to get version 1.1 of SCfO out with support for 9i. However, there were some significant problems that we had to overcome first. This post will concentrate on query execution time. When we first tested SCfO on a 9i server, after accounting for various changes to the data dictionary, we found that database registration was taking a long time. And I mean a looooooong time. The same database that on 10g or 11g would take a couple of minutes to register would be taking upwards of 30 mins on 9i. Obviously, this is not ideal, so a poke around the query execution plans was required. As an example, let's take the table population query - the one that reads ALL_TABLES and joins it with a few other dictionary views to get us back our list of tables. On 10g, this query takes 5.6 seconds. On 9i, it takes 89.47 seconds. The difference in execution plan is even more dramatic - here's the (edited) execution plan on 10g: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 108K| 939 || 1 | SORT ORDER BY | | 108K| 939 || 2 | NESTED LOOPS OUTER | | 108K| 938 ||* 3 | HASH JOIN RIGHT OUTER | | 103K| 762 || 4 | VIEW | ALL_EXTERNAL_LOCATIONS | 2058 | 3 ||* 20 | HASH JOIN RIGHT OUTER | | 73472 | 759 || 21 | VIEW | ALL_EXTERNAL_TABLES | 2097 | 3 ||* 34 | HASH JOIN RIGHT OUTER | | 39920 | 755 || 35 | VIEW | ALL_MVIEWS | 51 | 7 || 58 | NESTED LOOPS OUTER | | 39104 | 748 || 59 | VIEW | ALL_TABLES | 6704 | 668 || 89 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2025 | 5 || 106 | VIEW | ALL_PART_TABLES | 277 | 11 |------------------------------------------------------------------------------- And the same query on 9i: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 16P| 55G|| 1 | SORT ORDER BY | | 16P| 55G|| 2 | NESTED LOOPS OUTER | | 16P| 862M|| 3 | NESTED LOOPS OUTER | | 5251G| 992K|| 4 | NESTED LOOPS OUTER | | 4243M| 2578 || 5 | NESTED LOOPS OUTER | | 2669K| 1440 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 ||* 50 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2043 | ||* 66 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_TABLES | 1777K| ||* 80 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_LOCATIONS | 1744K| ||* 96 | VIEW | ALL_PART_TABLES | 852K| |------------------------------------------------------------------------------- Have a look at the cost column. 10g's overall query cost is 939, and 9i is 55,000,000,000 (or more precisely, 55,496,472,769). It's also having to process far more data. What on earth could be causing this huge difference in query cost? After trawling through the '10g New Features' documentation, we found item 1.9.2.21. Before 10g, Oracle advised that you do not collect statistics on data dictionary objects. From 10g, it advised that you do collect statistics on the data dictionary; for our queries, Oracle therefore knows what sort of data is in the dictionary tables, and so can generate an efficient execution plan. On 9i, no statistics are present on the system tables, so Oracle has to use the Rule Based Optimizer, which turns most LEFT JOINs into nested loops. If we force 9i to use hash joins, like 10g, we get a much better plan: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 7587K| 3704 || 1 | SORT ORDER BY | | 7587K| 3704 ||* 2 | HASH JOIN OUTER | | 7587K| 822 ||* 3 | HASH JOIN OUTER | | 5262K| 616 ||* 4 | HASH JOIN OUTER | | 2980K| 465 ||* 5 | HASH JOIN OUTER | | 710K| 432 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 || 50 | VIEW | ALL_PART_TABLES | 852K| 104 || 78 | VIEW | ALL_TAB_COMMENTS | 2043 | 14 || 93 | VIEW | ALL_EXTERNAL_LOCATIONS | 1744K| 31 || 106 | VIEW | ALL_EXTERNAL_TABLES | 1777K| 28 |------------------------------------------------------------------------------- That's much more like it. This drops the execution time down to 24 seconds. Not as good as 10g, but still an improvement. There are still several problems with this, however. 10g introduced a new join method - a right outer hash join (used in the first execution plan). The 9i query optimizer doesn't have this option available, so forcing a hash join means it has to hash the ALL_TABLES table, and furthermore re-hash it for every hash join in the execution plan; this could be thousands and thousands of rows. And although forcing hash joins somewhat alleviates this problem on our test systems, there's no guarantee that this will improve the execution time on customers' systems; it may even increase the time it takes (say, if all their tables are partitioned, or they've got a lot of materialized views). Ideally, we would want a solution that provides a speedup whatever the input. To try and get some ideas, we asked some oracle performance specialists to see if they had any ideas or tips. Their recommendation was to add a hidden hook into the product that allowed users to specify their own query hints, or even rewrite the queries entirely. However, we would prefer not to take that approach; as well as a lot of new infrastructure & a rewrite of the population code, it would have meant that any users of 9i would have to spend some time optimizing it to get it working on their system before they could use the product. Another approach was needed. All our population queries have a very specific pattern - a base table provides most of the information we need (ALL_TABLES for tables, or ALL_TAB_COLS for columns) and we do a left join to extra subsidiary tables that fill in gaps (for instance, ALL_PART_TABLES for partition information). All the left joins use the same set of columns to join on (typically the object owner & name), so we could re-use the hash information for each join, rather than re-hashing the same columns for every join. To allow us to do this, along with various other performance improvements that could be done for the specific query pattern we were using, we read all the tables individually and do a hash join on the client. Fortunately, this 'pure' algorithmic problem is the kind that can be very well optimized for expected real-world situations; as well as storing row data we're not using in the hash key on disk, we use very specific memory-efficient data structures to store all the information we need. This allows us to achieve a database population time that is as fast as on 10g, and even (in some situations) slightly faster, and a memory overhead of roughly 150 bytes per row of data in the result set (for schemas with 10,000 tables in that means an extra 1.4MB memory being used during population). Next: fun with the 9i dictionary views.

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  • Bridging Virtual Networking into Real LAN on a OpenNebula Cluster

    - by user101012
    I'm running Open Nebula with 1 Cluster Controller and 3 Nodes. I registered the nodes at the front-end controller and I can start an Ubuntu virtual machine on one of the nodes. However from my network I cannot ping the virtual machine. I am not quite sure if I have set up the virtual machine correctly. The Nodes all have a br0 interfaces which is bridged with eth0. The IP Address is in the 192.168.1.x range. The Template file I used for the vmnet is: NAME = "VM LAN" TYPE = RANGED BRIDGE = br0 # Replace br0 with the bridge interface from the cluster nodes NETWORK_ADDRESS = 192.168.1.128 # Replace with corresponding IP address NETWORK_SIZE = 126 NETMASK = 255.255.255.0 GATEWAY = 192.168.1.1 NS = 192.168.1.1 However, I cannot reach any of the virtual machines even though sunstone says that the virtual machine is running and onevm list also states that the vm is running. It might be helpful to know that we are using KVM as a hypervisor and I am not quite sure if the virbr0 interface which was automatically created when installing KVM might be a problem.

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  • GlassFish cluster-targeted jdbc is not enabled

    - by Jin Kwon
    I have a GlassFish cluster. When I tried to add node and a instance, DAS saids a bunch of error messages telling Resource [ jdbc/xxxx ] of type [ jdbc ] is not enabled [#|2012-11-14T12:07:04.318+0900|SEVERE|glassfish3.1.2|javax.enterprise.system.core.com.sun.enterprise.v3.server|_ThreadID=2803;_ThreadName=Thread-2;|java.lang.StackOverflowError at java.io.FileOutputStream.writeBytes(Native Method) at java.io.FileOutputStream.write(FileOutputStream.java:318) at java.io.BufferedOutputStream.write(BufferedOutputStream.java:122) at java.io.PrintStream.write(PrintStream.java:480) at sun.nio.cs.StreamEncoder.writeBytes(StreamEncoder.java:221) at sun.nio.cs.StreamEncoder.implFlushBuffer(StreamEncoder.java:291) at sun.nio.cs.StreamEncoder.implFlush(StreamEncoder.java:295) at sun.nio.cs.StreamEncoder.flush(StreamEncoder.java:141) at java.io.OutputStreamWriter.flush(OutputStreamWriter.java:229) at java.util.logging.StreamHandler.flush(StreamHandler.java:242) at java.util.logging.ConsoleHandler.publish(ConsoleHandler.java:106) at java.util.logging.Logger.log(Logger.java:522) at com.sun.logging.LogDomains$1.log(LogDomains.java:372) at java.util.logging.Logger.doLog(Logger.java:543) at java.util.logging.Logger.log(Logger.java:607) at com.sun.enterprise.resource.deployer.JdbcResourceDeployer.deployResource(JdbcResourceDeployer.java:117) at org.glassfish.javaee.services.ResourceProxy.create(ResourceProxy.java:90) at com.sun.enterprise.naming.impl.SerialContext.lookup(SerialContext.java:507) at com.sun.enterprise.naming.impl.SerialContext.lookup(SerialContext.java:455) at javax.naming.InitialContext.lookup(InitialContext.java:411) at javax.naming.InitialContext.lookup(InitialContext.java:411) at com.sun.appserv.connectors.internal.api.ResourceNamingService.lookup(ResourceNamingService.java:221) the JDBC Resource is ok and targeted with the cluster. I've installed the JDBC driver on the new node. Can anybody help?

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  • How To Set Up A Loadbalanced High-Availability Apache Cluster On Windows

    - by bReAd
    Setting up a two-node Apache web server cluster that provides high-availability. In front of the Apache cluster we create a load balancer that splits up incoming requests between the two Apache nodes. Because we do not want the load balancer to become another “Single Point Of Failure”, we must provide high-availability for the load balancer, too. Therefore our load balancer will in fact consist out of two load balancer nodes that monitor each other using heartbeat, and if one load balancer fails, the other takes over silently. The following setup is proposed: Apache node 1: webserver1.example.com (webserver1) – IP address: 192.168.0.101; Apache document root: /var/www Apache node 2: webserver2.example.com (webserver2) – IP address: 192.168.0.102; Apache document root: /var/www Load Balancer node 1: loadb1.example.com (loadb1) – IP address: 192.168.0.103 Load Balancer node 2: loadb2.example.com (loadb2) – IP address: 192.168.0.104 Virtual IP Address: 192.168.0.105 (used for incoming requests) Currently, there are many solutions for Linux machines and there aren't any on windows. I've tried searching a long time for solutions on Windows platform How do I create the virtual IP in windows and perform monitoring and make the load balancer listen to the virtual IP Address?

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