Search Results

Search found 2646 results on 106 pages for 'fetch'.

Page 96/106 | < Previous Page | 92 93 94 95 96 97 98 99 100 101 102 103  | Next Page >

  • Multicast hostname lookups on OSX

    - by KARASZI István
    I have a problem with hostname lookups on my OSX computer. According to Apple's HK3473 document it says for v10.6: Host names that contain only one label in addition to local, for example "My-Computer.local", are resolved using Multicast DNS (Bonjour) by default. Host names that contain two or more labels in addition to local, for example "server.domain.local", are resolved using a DNS server by default. Which is not true as my testing. If I try to open a connection on my local computer to a remote port: telnet example.domain.local 22 then it will lookup the IP address with multicast DNS next to the A and AAAA lookups. This causes a two seconds lookup timeout on every lookup. Which is a lot! When I try with IPv4 only then it won't use the multicast queries to fetch the remote address just the simple A queries. telnet -4 example.domain.local 22 When I try with IPv6 only: telnet -6 example.domain.local 22 then it will lookup with multicast DNS and AAAA again, and the 2 seconds timeout delay occurs again. I've tried to create a resolver entry to my /etc/resolver/domain.local, and /etc/resolver/local.1, but none of them was working. Is there any way to disable this multicast lookups for the "two or more label addition to local" domains, or simply disable it for the selected subdomain (domain.local)? Thank you! Update #1 Thanks @mralexgray for the scutil --dns command, now I can see my domain in the list, but it's late in the order: DNS configuration resolver #1 domain : adverticum.lan nameserver[0] : 192.168.1.1 order : 200000 resolver #2 domain : local options : mdns timeout : 2 order : 300000 resolver #3 domain : 254.169.in-addr.arpa options : mdns timeout : 2 order : 300200 resolver #4 domain : 8.e.f.ip6.arpa options : mdns timeout : 2 order : 300400 resolver #5 domain : 9.e.f.ip6.arpa options : mdns timeout : 2 order : 300600 resolver #6 domain : a.e.f.ip6.arpa options : mdns timeout : 2 order : 300800 resolver #7 domain : b.e.f.ip6.arpa options : mdns timeout : 2 order : 301000 resolver #8 domain : domain.local nameserver[0] : 192.168.1.1 order : 200001 Maybe it would work if I could move the resolver #8 to the position #2. Update #2 No probably won't work because the local DNS server on 192.168.1.1 answering for domain.local requests and it's before the mDNS (resolver #2). Update #3 I could decrease the mDNS timeout in /System/Library/SystemConfiguration/IPMonitor.bundle/Contents/Info.plist file, which speeds up the lookups a little, but this is not the solution.

    Read the article

  • OpenVPN multiple servers on the same subnet, high availability

    - by andre
    Hey everyone. Let me start by saying that my Linux experience isn't super awesome but I can usually find my way around things easily. Over at work we have an OpenVPN setup that's been due for some improvement for a while now. The main server (tap mode) runs in our office, behind a rather slow DSL connection. The main problem is that, since I'm usually out of the office, every time I want to access something on the virtual network I have to go through that server to get anywhere else. We have two servers up on 100 Mbit connections that we use for development and production purposes, about 3 more servers in the office (one of them behind a different T1 line for VOIP) and about two dozen clients who use the network on a daily basis from various locations. We've had situations where network routing (outside of our control) would not allow people to reach our main OpenVPN server whilst the other locations were connectable. Also any time someone outside the office wants to fetch something from any of the servers (say, a 500 MB code repository), a whopping 20 KB/s download speed is just unacceptable these days (did I mention slow DSL? ok). We had to implement traffic shaping on this server since maxing out this connection was fairly trivial. I had the thought of running two (or more) OpenVPN servers in the network. These would have to have the same subnet though, as our application relies on virtual network's IP addresses for some of its core functionality. The clients would also preferably retain the same IP addresses but that's not vital. For simplicity, lets call the current server office and the second server I'm setting up, cloud. Call the server on the T1 phone. This proved to be rather complex because as soon as I connect to cloud, I cannot see office. Any routes to a server that would go through office also do not work while I'm connected to cloud (no ping, nothing) and vice-versa. There's no rules for iptables that would be blocking the traffic either. Recently I came across this article on linuxjournal but the solution they provide seems to only cover the use of two servers and somewhat outdated (can't even find much documentation, their wiki is offline). They also state that adding more servers would be a complex task. Ideally I would like to keep the existing server office running the virtual network and also run the OpenVPN daemon on the cloud and phone servers (100 Mbit and very reliable connection, respectively) so that we're on safe ground in case of a hardware failure, DSL failure, etc. So, in essence, I'm looking for a highly available OpenVPN solution (fix, patch, hack, tweak, whatever you want to call it) that will accept connections on multiple hosts (2 or more) whilst keeping the same IP address subnet regardless of the server to which you connect to. Thanks for reading and sorry for the long post, I hope it gets the point across :P

    Read the article

  • Rebasing a branch which is public

    - by Dror
    I'm failing to understand how to use git-rebase, and I consider the following example. Let's start a repository in ~/tmp/repo: $ git init Then add a file foo $ echo "hello world" > foo which is then added and committed: $ git add foo $ git commit -m "Added foo" Next, I started a remote repository. In ~/tmp/bare.git I ran $ git init --bare In order to link repo to bare.git I ran $ git remote add origin ../bare.git/ $ git push --set-upstream origin master Next, lets branch, add a file and set an upstream for the new branch b1: $ git checkout -b b1 $ echo "bar" > foo2 $ git add foo2 $ git commit -m "add foo2 in b1" $ git push --set-upstream origin b1 Now it is time to switch back to master and change something there: $ echo "change foo" > foo $ git commit -a -m "changed foo in master" $ git push At this point in master the file foo contain changed foo, while in b1 it is still hello world. Finally, I want to sync b1 with the progress made in master. $ git checkout b1 $ git fetch origin $ git rebase origin/master At this point git st returns: # On branch b1 # Your branch and 'origin/b1' have diverged, # and have 2 and 1 different commit each, respectively. # (use "git pull" to merge the remote branch into yours) # nothing to commit, working directory clean At this point the content of foo in the branch b1 is change foo as well. So what does this warning mean? I expected I should do a git push, git suggests to do git pull... According to this answer, this is more or less it, and in his comment @FrerichRaabe explicitly say that I don't need to do a pull. What's going on here? What is the danger, how should one proceed? How should the history be kept consistent? What is the interplay between the case described above and the following citation: Do not rebase commits that you have pushed to a public repository. taken from pro git book. I guess it is somehow related, and if not I would love to know why. What's the relation between the above scenario and the procedure I described in this post.

    Read the article

  • How to circumvent ISP Limiting "Unknown" traffic - (SSH)Proxy, VPN

    - by connery
    I am having issues with using a proxy/VPN, with my current ISP (Comenersol, Spain). From my point of view they limit traffic by protocol or by traffic they "know" and "dont know". I'll explain my findings so far below. Internet connection in Spain: ~400-420KByte/sec (speedtest.net) OpenVPN Server in Sweden(pfsense): 100/100Mbit. LZO Compression. TCP. Tun. Aes128 Squid Proxy server in Sweden (pfsense): 100/100 (same box as the vpn server). Plain, no encryption. Runs in stealth mode to hide the use of proxy. NOT running OpenVPN or Squid Proxy, this is my findings: When I download a file from my pfsense box in Sweden, I get maximum speed When I run speedtest.net and choose any european server (including Swedish), I get max speed When I download a torrent (with non default port above 10K), I get limited to ~100KByte/sec. Encryption is turned off If I download something through https, I get max speed Running either Squid Proxy or VPN, this is my findings When I download a file from my pfsense box in Sweden, I get ~100KByte/sec When I run speedtest.net and choose any european server (including Swedish and Spanish), I get ~100Kbyte/sec When I download a torrent, I get same limitation ~100KByte/sec When I download something through https, I get ~100KByte/sec I verify the speeds above with speedtest.net measure, firefox measure in addition to having bmon running in terminal in the background. This way I am certain that the speeds I get presented, are in fact correct. If I connect through a different ISP with VPN or Squid Proxy, I get better speeds (400KByte/sec ++) In short: Whenever I tunnel my traffic through Sweden, my SPanish ISP throttles the traffic. I thought tunneling it through Squid would solve the issue, since I then would no longer hide my traffic through encryption. This does not seem to be the case. Wget and fetch gives same result. I did not try 'nc', but I assume this would give the same result. Does anyone know how to circumvent this issue? I would very much like to be able to get full speed with Swedish ip, as this would make me able to stream TV at higher quality than today. 100KByte/sec just does not cut it quality wise. Thanks for reading. Looking forward for your help.

    Read the article

  • SMBfs mounting OK, listing OK, Read KO, smbclient OK

    - by Kwaio
    I've tried to make the title the most meaningfull I could but it still looks ugly. The premises. We are using RHEL3-U8 as OS on most servers here, don't ask me why or suggest to upgrade, it's not on today's schedule. That means kernel used is 2.4.21 I have no access to the remote server, but I know it is a netApp NAS rack. $> smbclient --version Version 3.0.9-1.3E.9 Here is the /etc/fstab line : //NASHOSTNAME/share /mnt/mydir smbfs ro,uid=123,gid=123,workgroup=XXXX,credentials=/somefile 0 0 Here is the following mount output line //NASHOSTNAME/share on /mnt/mydir type smbfs (0) The symptoms. I can list the share without problems, even cd in there. The issue appears if I try to read any file : $> cat /mnt/mydir/fileX.txt cat: /mnt/mydir/fileX.txt: Input/output error In the system logs (/var/log/kernel for example) the following errors appear. Jul 30 15:40:02 hostname kernel: smb_errno: class ERRHRD, code 31 from command 0x2 Jul 30 15:40:02 hostname kernel: smb_errno: class ERRHRD, code 31 from command 0x2 Jul 30 15:40:02 hostname kernel: smb_open: fileX.txt open failed, result=-5 Jul 30 15:40:02 hostname kernel: smb_errno: class ERRHRD, code 31 from command 0x2 Jul 30 15:40:02 hostname kernel: smb_errno: class ERRHRD, code 31 from command 0x2 Jul 30 15:40:02 hostname kernel: smb_open: fileX.txt open failed, result=-5 Jul 30 15:40:02 hostname kernel: smb_readpage_sync: fileX.txt open failed, error=-5 The ERRHRD code 0x001F error is "General hardware failure" although it seems samba sometimes uses it for a different purpose, see http://www.ubiqx.org/cifs/SMB.html [Strange behaviour Alert] Additionnal informations : There is another SMB mountpoint on the system pointing to a (linux) host using samba and this one works. What I have tried. I have tried adding debug=4 to the mounting options and remounting the share and the logs still look the same. I have tried to mount the share with smbclient and I am able to fetch files with the get command. Both targets are in the same subnet, so network problem should be out, even if the LAN goes through a VPN with optimizers, MTU has already been decreased to 1450. I can also mount the share through NFS but then the files are all root.root 700 and I need to read them with another user...

    Read the article

  • How can I resolve Hibernate 3's ConstraintViolationException when updating a Persistent Entity's Col

    - by Tim Visher
    I'm trying to discover why two nearly identical class sets are behaving different from Hibernate 3's perspective. I'm fairly new to Hibernate in general and I'm hoping I'm missing something fairly obvious about the mappings or timing issues or something along those lines but I spent the whole day yesterday staring at the two sets and any differences that would lead to one being able to be persisted and the other not completely escaped me. I appologize in advance for the length of this question but it all hinges around some pretty specific implementation details. I have the following class mapped with Annotations and managed by Hibernate 3.? (if the specific specific version turns out to be pertinent, I'll figure out what it is). Java version is 1.6. ... @Embeddable public class JobStateChange implements Comparable<JobStateChange> { @Temporal(TemporalType.TIMESTAMP) @Column(nullable = false) private Date date; @Enumerated(EnumType.STRING) @Column(nullable = false, length = JobState.FIELD_LENGTH) private JobState state; @ManyToOne(fetch = FetchType.LAZY) @JoinColumn(name = "acting_user_id", nullable = false) private User actingUser; public JobStateChange() { } @Override public int compareTo(final JobStateChange o) { return this.date.compareTo(o.date); } @Override public boolean equals(final Object obj) { if (this == obj) { return true; } else if (!(obj instanceof JobStateChange)) { return false; } JobStateChange candidate = (JobStateChange) obj; return this.state == candidate.state && this.actingUser.equals(candidate.getUser()) && this.date.equals(candidate.getDate()); } @Override public int hashCode() { return this.state.hashCode() + this.actingUser.hashCode() + this.date.hashCode(); } } It is mapped as a Hibernate CollectionOfElements in the class Job as follows: ... @Entity @Table( name = "job", uniqueConstraints = { @UniqueConstraint( columnNames = { "agency", //Job Name "payment_type", //Job Name "payment_file", //Job Name "date_of_payment", "payment_control_number", "truck_number" }) }) public class Job implements Serializable { private static final long serialVersionUID = -1131729422634638834L; ... @org.hibernate.annotations.CollectionOfElements @JoinTable(name = "job_state", joinColumns = @JoinColumn(name = "job_id")) @Sort(type = SortType.NATURAL) private final SortedSet<JobStateChange> stateChanges = new TreeSet<JobStateChange>(); ... public void advanceState( final User actor, final Date date) { JobState nextState; LOGGER.debug("Current state of {} is {}.", this, this.getCurrentState()); if (null == this.currentState) { nextState = JobState.BEGINNING; } else { if (!this.isAdvanceable()) { throw new IllegalAdvancementException(this.currentState.illegalAdvancementStateMessage); } if (this.currentState.isDivergent()) { nextState = this.currentState.getNextState(this); } else { nextState = this.currentState.getNextState(); } } JobStateChange stateChange = new JobStateChange(nextState, actor, date); this.setCurrentState(stateChange.getState()); this.stateChanges.add(stateChange); LOGGER.debug("Advanced {} to {}", this, this.getCurrentState()); } private void setCurrentState(final JobState jobState) { this.currentState = jobState; } boolean isAdvanceable() { return this.getCurrentState().isAdvanceable(this); } ... @Override public boolean equals(final Object obj) { if (obj == this) { return true; } else if (!(obj instanceof Job)) { return false; } Job otherJob = (Job) obj; return this.getName().equals(otherJob.getName()) && this.getDateOfPayment().equals(otherJob.getDateOfPayment()) && this.getPaymentControlNumber().equals(otherJob.getPaymentControlNumber()) && this.getTruckNumber().equals(otherJob.getTruckNumber()); } @Override public int hashCode() { return this.getName().hashCode() + this.getDateOfPayment().hashCode() + this.getPaymentControlNumber().hashCode() + this.getTruckNumber().hashCode(); } ... } The purpose of JobStateChange is to record when the Job moves through a series of State Changes that are outline in JobState as enums which know about advancement and decrement rules. The interface used to advance Jobs through a series of states is to call Job.advanceState() with a Date and a User. If the Job is advanceable according to rules coded in the enum, then a new StateChange is added to the SortedSet and everyone's happy. If not, an IllegalAdvancementException is thrown. The DDL this generates is as follows: ... drop table job; drop table job_state; ... create table job ( id bigint generated by default as identity, current_state varchar(25), date_of_payment date not null, beginningCheckNumber varchar(8) not null, item_count integer, agency varchar(10) not null, payment_file varchar(25) not null, payment_type varchar(25) not null, endingCheckNumber varchar(8) not null, payment_control_number varchar(4) not null, truck_number varchar(255) not null, wrapping_system_type varchar(15) not null, printer_id bigint, primary key (id), unique (agency, payment_type, payment_file, date_of_payment, payment_control_number, truck_number) ); create table job_state ( job_id bigint not null, acting_user_id bigint not null, date timestamp not null, state varchar(25) not null, primary key (job_id, acting_user_id, date, state) ); ... alter table job add constraint FK19BBD12FB9D70 foreign key (printer_id) references printer; alter table job_state add constraint FK57C2418FED1F0D21 foreign key (acting_user_id) references app_user; alter table job_state add constraint FK57C2418FABE090B3 foreign key (job_id) references job; ... The database is seeded with the following data prior to running tests ... insert into job (id, agency, payment_type, payment_file, payment_control_number, date_of_payment, beginningCheckNumber, endingCheckNumber, item_count, current_state, printer_id, wrapping_system_type, truck_number) values (-3, 'RRB', 'Monthly', 'Monthly','4501','1998-12-01 08:31:16' , '00000001','00040000', 40000, 'UNASSIGNED', null, 'KERN', '02'); insert into job_state (job_id, acting_user_id, date, state) values (-3, -1, '1998-11-30 08:31:17', 'UNASSIGNED'); ... After the database schema is automatically generated and rebuilt by the Hibernate tool. The following test runs fine up until the call to Session.flush() ... @ContextConfiguration(locations = { "/applicationContext-data.xml", "/applicationContext-service.xml" }) public class JobDaoIntegrationTest extends AbstractTransactionalJUnit4SpringContextTests { @Autowired private JobDao jobDao; @Autowired private SessionFactory sessionFactory; @Autowired private UserService userService; @Autowired private PrinterService printerService; ... @Test public void saveJob_JobAdvancedToAssigned_AllExpectedStateChanges() { //Get an unassigned Job Job job = this.jobDao.getJob(-3L); assertEquals(JobState.UNASSIGNED, job.getCurrentState()); Date advancedToUnassigned = new GregorianCalendar(1998, 10, 30, 8, 31, 17).getTime(); assertEquals(advancedToUnassigned, job.getStateChange(JobState.UNASSIGNED).getDate()); //Satisfy advancement constraints and advance job.setPrinter(this.printerService.getPrinter(-1L)); Date advancedToAssigned = new Date(); job.advanceState( this.userService.getUserByUsername("admin"), advancedToAssigned); assertEquals(JobState.ASSIGNED, job.getCurrentState()); assertEquals(advancedToUnassigned, job.getStateChange(JobState.UNASSIGNED).getDate()); assertEquals(advancedToAssigned, job.getStateChange(JobState.ASSIGNED).getDate()); //Persist to DB this.sessionFactory.getCurrentSession().flush(); ... } ... } The error thrown is SQLCODE=-803, SQLSTATE=23505: could not insert collection rows: [jaci.model.job.Job.stateChanges#-3] org.hibernate.exception.ConstraintViolationException: could not insert collection rows: [jaci.model.job.Job.stateChanges#-3] at org.hibernate.exception.SQLStateConverter.convert(SQLStateConverter.java:94) at org.hibernate.exception.JDBCExceptionHelper.convert(JDBCExceptionHelper.java:66) at org.hibernate.persister.collection.AbstractCollectionPersister.insertRows(AbstractCollectionPersister.java:1416) at org.hibernate.action.CollectionUpdateAction.execute(CollectionUpdateAction.java:86) at org.hibernate.engine.ActionQueue.execute(ActionQueue.java:279) at org.hibernate.engine.ActionQueue.executeActions(ActionQueue.java:263) at org.hibernate.engine.ActionQueue.executeActions(ActionQueue.java:170) at org.hibernate.event.def.AbstractFlushingEventListener.performExecutions(AbstractFlushingEventListener.java:321) at org.hibernate.event.def.DefaultFlushEventListener.onFlush(DefaultFlushEventListener.java:50) at org.hibernate.impl.SessionImpl.flush(SessionImpl.java:1027) at jaci.dao.JobDaoIntegrationTest.saveJob_JobAdvancedToAssigned_AllExpectedStateChanges(JobDaoIntegrationTest.java:98) at org.springframework.test.context.junit4.SpringTestMethod.invoke(SpringTestMethod.java:160) at org.springframework.test.context.junit4.SpringMethodRoadie.runTestMethod(SpringMethodRoadie.java:233) at org.springframework.test.context.junit4.SpringMethodRoadie$RunBeforesThenTestThenAfters.run(SpringMethodRoadie.java:333) at org.springframework.test.context.junit4.SpringMethodRoadie.runWithRepetitions(SpringMethodRoadie.java:217) at org.springframework.test.context.junit4.SpringMethodRoadie.runTest(SpringMethodRoadie.java:197) at org.springframework.test.context.junit4.SpringMethodRoadie.run(SpringMethodRoadie.java:143) at org.springframework.test.context.junit4.SpringJUnit4ClassRunner.invokeTestMethod(SpringJUnit4ClassRunner.java:160) at org.springframework.test.context.junit4.SpringJUnit4ClassRunner.run(SpringJUnit4ClassRunner.java:97) Caused by: com.ibm.db2.jcc.b.lm: DB2 SQL Error: SQLCODE=-803, SQLSTATE=23505, SQLERRMC=1;ACI_APP.JOB_STATE, DRIVER=3.50.152 at com.ibm.db2.jcc.b.wc.a(wc.java:575) at com.ibm.db2.jcc.b.wc.a(wc.java:57) at com.ibm.db2.jcc.b.wc.a(wc.java:126) at com.ibm.db2.jcc.b.tk.b(tk.java:1593) at com.ibm.db2.jcc.b.tk.c(tk.java:1576) at com.ibm.db2.jcc.t4.db.k(db.java:353) at com.ibm.db2.jcc.t4.db.a(db.java:59) at com.ibm.db2.jcc.t4.t.a(t.java:50) at com.ibm.db2.jcc.t4.tb.b(tb.java:200) at com.ibm.db2.jcc.b.uk.Gb(uk.java:2355) at com.ibm.db2.jcc.b.uk.e(uk.java:3129) at com.ibm.db2.jcc.b.uk.zb(uk.java:568) at com.ibm.db2.jcc.b.uk.executeUpdate(uk.java:551) at org.hibernate.jdbc.NonBatchingBatcher.addToBatch(NonBatchingBatcher.java:46) at org.hibernate.persister.collection.AbstractCollectionPersister.insertRows(AbstractCollectionPersister.java:1389) Therein lies my problem… A nearly identical Class set (in fact, so identical that I've been chomping at the bit to make it a single class that serves both business entities) runs absolutely fine. It is identical except for name. Instead of Job it's Web. Instead of JobStateChange it's WebStateChange. Instead of JobState it's WebState. Both Job and Web's SortedSet of StateChanges are mapped as a Hibernate CollectionOfElements. Both are @Embeddable. Both are SortType.Natural. Both are backed by an Enumeration with some advancement rules in it. And yet when a nearly identical test is run for Web, no issue is discovered and the data flushes fine. For the sake of brevity I won't include all of the Web classes here, but I will include the test and if anyone wants to see the actual sources, I'll include them (just leave a comment). The data seed: insert into web (id, stock_type, pallet, pallet_id, date_received, first_icn, last_icn, shipment_id, current_state) values (-1, 'PF', '0011', 'A', '2008-12-31 08:30:02', '000000001', '000080000', -1, 'UNSTAGED'); insert into web_state (web_id, date, state, acting_user_id) values (-1, '2008-12-31 08:30:03', 'UNSTAGED', -1); The test: ... @ContextConfiguration(locations = { "/applicationContext-data.xml", "/applicationContext-service.xml" }) public class WebDaoIntegrationTest extends AbstractTransactionalJUnit4SpringContextTests { @Autowired private WebDao webDao; @Autowired private UserService userService; @Autowired private SessionFactory sessionFactory; ... @Test public void saveWeb_WebAdvancedToNewState_AllExpectedStateChanges() { Web web = this.webDao.getWeb(-1L); Date advancedToUnstaged = new GregorianCalendar(2008, 11, 31, 8, 30, 3).getTime(); assertEquals(WebState.UNSTAGED, web.getCurrentState()); assertEquals(advancedToUnstaged, web.getState(WebState.UNSTAGED).getDate()); Date advancedToStaged = new Date(); web.advanceState( this.userService.getUserByUsername("admin"), advancedToStaged); this.sessionFactory.getCurrentSession().flush(); web = this.webDao.getWeb(web.getId()); assertEquals( "Web should have moved to STAGED State.", WebState.STAGED, web.getCurrentState()); assertEquals(advancedToUnstaged, web.getState(WebState.UNSTAGED).getDate()); assertEquals(advancedToStaged, web.getState(WebState.STAGED).getDate()); assertNotNull(web.getState(WebState.UNSTAGED)); assertNotNull(web.getState(WebState.STAGED)); } ... } As you can see, I assert that the Web was reconstituted the way I expect, I advance it, flush it to the DB, and then re-get it and verify that the states are as I expect. Everything works perfectly. Not so with Job. A possibly pertinent detail: the reconstitution code works fine if I cease to map JobStateChange.data as a TIMESTAMP and instead as a DATE, and ensure that all of the StateChanges always occur on different Dates. The problem is that this particular business entity can go through many state changes in a single day and so it needs to be sorted by time stamp rather than by date. If I don't do this then I can't sort the StateChanges correctly. That being said, WebStateChange.date is also mapped as a TIMESTAMP and so I again remain absolutely befuddled as to where this error is arising from. I tried to do a fairly thorough job of giving all of the technical details of the implementation but as this particular question is very implementation specific, if I missed anything just let me know in the comments and I'll include it. Thanks so much for your help! UPDATE: Since it turns out to be important to the solution of my problem, I have to include the pertinent bits of the WebStateChange class as well. ... @Embeddable public class WebStateChange implements Comparable<WebStateChange> { @Temporal(TemporalType.TIMESTAMP) @Column(nullable = false) private Date date; @Enumerated(EnumType.STRING) @Column(nullable = false, length = WebState.FIELD_LENGTH) private WebState state; @ManyToOne(fetch = FetchType.LAZY) @JoinColumn(name = "acting_user_id", nullable = false) private User actingUser; ... WebStateChange( final WebState state, final User actingUser, final Date date) { ExceptionUtils.illegalNullArgs(state, actingUser, date); this.state = state; this.actingUser = actingUser; this.date = new Date(date.getTime()); } @Override public int compareTo(final WebStateChange otherStateChange) { return this.date.compareTo(otherStateChange.date); } @Override public boolean equals(final Object candidate) { if (this == candidate) { return true; } else if (!(candidate instanceof WebStateChange)) { return false; } WebStateChange candidateWebState = (WebStateChange) candidate; return this.getState() == candidateWebState.getState() && this.getUser().equals(candidateWebState.getUser()) && this.getDate().equals(candidateWebState.getDate()); } @Override public int hashCode() { return this.getState().hashCode() + this.getUser().hashCode() + this.getDate().hashCode(); } ... }

    Read the article

  • SQL SERVER – Signal Wait Time Introduction with Simple Example – Wait Type – Day 2 of 28

    - by pinaldave
    In this post, let’s delve a bit more in depth regarding wait stats. The very first question: when do the wait stats occur? Here is the simple answer. When SQL Server is executing any task, and if for any reason it has to wait for resources to execute the task, this wait is recorded by SQL Server with the reason for the delay. Later on we can analyze these wait stats to understand the reason the task was delayed and maybe we can eliminate the wait for SQL Server. It is not always possible to remove the wait type 100%, but there are few suggestions that can help. Before we continue learning about wait types and wait stats, we need to understand three important milestones of the query life-cycle. Running - a query which is being executed on a CPU is called a running query. This query is responsible for CPU time. Runnable – a query which is ready to execute and waiting for its turn to run is called a runnable query. This query is responsible for Signal Wait time. (In other words, the query is ready to run but CPU is servicing another query). Suspended – a query which is waiting due to any reason (to know the reason, we are learning wait stats) to be converted to runnable is suspended query. This query is responsible for wait time. (In other words, this is the time we are trying to reduce). In simple words, query execution time is a summation of the query Executing CPU Time (Running) + Query Wait Time (Suspended) + Query Signal Wait Time (Runnable). Again, it may be possible a query goes to all these stats multiple times. Let us try to understand the whole thing with a simple analogy of a taxi and a passenger. Two friends, Tom and Danny, go to the mall together. When they leave the mall, they decide to take a taxi. Tom and Danny both stand in the line waiting for their turn to get into the taxi. This is the Signal Wait Time as they are ready to get into the taxi but the taxis are currently serving other customer and they have to wait for their turn. In other word they are in a runnable state. Now when it is their turn to get into the taxi, the taxi driver informs them he does not take credit cards and only cash is accepted. Neither Tom nor Danny have enough cash, they both cannot get into the vehicle. Tom waits outside in the queue and Danny goes to ATM to fetch the cash. During this time the taxi cannot wait, they have to let other passengers get into the taxi. As Tom and Danny both are outside in the queue, this is the Query Wait Time and they are in the suspended state. They cannot do anything till they get the cash. Once Danny gets the cash, they are both standing in the line again, creating one more Signal Wait Time. This time when their turn comes they can pay the taxi driver in cash and reach their destination. The time taken for the taxi to get from the mall to the destination is running time (CPU time) and the taxi is running. I hope this analogy is bit clear with the wait stats. You can check the Signalwait stats using following query of Glenn Berry. -- Signal Waits for instance SELECT CAST(100.0 * SUM(signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%signal (cpu) waits], CAST(100.0 * SUM(wait_time_ms - signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%resource waits] FROM sys.dm_os_wait_stats OPTION (RECOMPILE); Higher the Signal wait stats are not good for the system. Very high value indicates CPU pressure. In my experience, when systems are running smooth and without any glitch the Signal wait stat is lower than 20%. Again, this number can be debated (and it is from my experience and is not documented anywhere). In other words, lower is better and higher is not good for the system. In future articles we will discuss in detail the various wait types and wait stats and their resolution. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

    Read the article

  • SQL SERVER – Single Wait Time Introduction with Simple Example – Wait Type – Day 2 of 28

    - by pinaldave
    In this post, let’s delve a bit more in depth regarding wait stats. The very first question: when do the wait stats occur? Here is the simple answer. When SQL Server is executing any task, and if for any reason it has to wait for resources to execute the task, this wait is recorded by SQL Server with the reason for the delay. Later on we can analyze these wait stats to understand the reason the task was delayed and maybe we can eliminate the wait for SQL Server. It is not always possible to remove the wait type 100%, but there are few suggestions that can help. Before we continue learning about wait types and wait stats, we need to understand three important milestones of the query life-cycle. Running - a query which is being executed on a CPU is called a running query. This query is responsible for CPU time. Runnable – a query which is ready to execute and waiting for its turn to run is called a runnable query. This query is responsible for Single Wait time. (In other words, the query is ready to run but CPU is servicing another query). Suspended – a query which is waiting due to any reason (to know the reason, we are learning wait stats) to be converted to runnable is suspended query. This query is responsible for wait time. (In other words, this is the time we are trying to reduce). In simple words, query execution time is a summation of the query Executing CPU Time (Running) + Query Wait Time (Suspended) + Query Single Wait Time (Runnable). Again, it may be possible a query goes to all these stats multiple times. Let us try to understand the whole thing with a simple analogy of a taxi and a passenger. Two friends, Tom and Danny, go to the mall together. When they leave the mall, they decide to take a taxi. Tom and Danny both stand in the line waiting for their turn to get into the taxi. This is the Signal Wait Time as they are ready to get into the taxi but the taxis are currently serving other customer and they have to wait for their turn. In other word they are in a runnable state. Now when it is their turn to get into the taxi, the taxi driver informs them he does not take credit cards and only cash is accepted. Neither Tom nor Danny have enough cash, they both cannot get into the vehicle. Tom waits outside in the queue and Danny goes to ATM to fetch the cash. During this time the taxi cannot wait, they have to let other passengers get into the taxi. As Tom and Danny both are outside in the queue, this is the Query Wait Time and they are in the suspended state. They cannot do anything till they get the cash. Once Danny gets the cash, they are both standing in the line again, creating one more Single Wait Time. This time when their turn comes they can pay the taxi driver in cash and reach their destination. The time taken for the taxi to get from the mall to the destination is running time (CPU time) and the taxi is running. I hope this analogy is bit clear with the wait stats. You can check the single wait stats using following query of Glenn Berry. -- Signal Waits for instance SELECT CAST(100.0 * SUM(signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%signal (cpu) waits], CAST(100.0 * SUM(wait_time_ms - signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%resource waits] FROM sys.dm_os_wait_stats OPTION (RECOMPILE); Higher the single wait stats are not good for the system. Very high value indicates CPU pressure. In my experience, when systems are running smooth and without any glitch the single wait stat is lower than 20%. Again, this number can be debated (and it is from my experience and is not documented anywhere). In other words, lower is better and higher is not good for the system. In future articles we will discuss in detail the various wait types and wait stats and their resolution. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

    Read the article

  • Logical Domain Modeling Made Simple

    - by Knut Vatsendvik
    How can logical domain modeling be made simple and collaborative? Many non-technical end-users, managers and business domain experts find it difficult to understand the visual models offered by many UML tools. This creates trouble in capturing and verifying the information that goes into a logical domain model. The tools are also too advanced and complex for a non-technical user to learn and use. We have therefore, in our current project, ended up with using Confluence as tool for designing the logical domain model with the help of a few very useful plugins. Big thanks to Ole Nymoen and Per Spilling for their expertise in this field that made this posting possible. Confluence Plugins Here is a list of Confluence plugins used in this solution. Install these before trying out the macros used below. Plugin Description Copy Space Allows a space administrator to copy a space, including the pages within the space Metadata Supports adding metadata to Wiki pages Label Manages labeling of pages Linking Contains macros for linking to templates, the dashboard and other Table Enhances the table capability in Confluence Creating a Confluence Space First we need to create a new confluence space for the domain model. Click the link Create a Space located below the list of spaces on the Dashboard. Please contact your Confluence administrator is you do not have permissions to do this.   For illustrative purpose all attributes and entities in this posting are based on my imaginary project manager domain model. When a logical domain model is good enough for being implemented, do a copy of the Confluence Space (see Copy Space plugin). In this way you create a stable version of the logical domain model while further design can continue with the new copied space. Typical will the implementation phase result in a database design and/or a XSD schema design. Add Space Templates Go to the Home page of your Confluence Space. Navigate to the Browse drop-down menu and click on Advanced. Then click the Templates option in the left navigation panel. Click Add New Space Template to add the following three templates. Name: attribute {metadata-list} || Name | | || Type | | || Format | | || Description | | {metadata-list} {add-label:attribute} Name: primary-type {metadata-list} || Name | || || Type | || || Format | || || Description | || {metadata-list} {add-label:primary-type} Name: complex-type {metadata-list} || Name | || || Description |  || {metadata-list} h3. Attributes || Name || Type || Format || Description || | [name] | {metadata-from:name|Type} | {metadata-from:name|Format} | {metadata-from:name|Description} | {add-label:complex-type,entity} The metadata-list macro (see Metadata plugin) will save a list of metadata values to the page. The add-label macro (see Label plugin) will automatically label the page. Primary Types Page Our first page to add will act as container for our primary types. Switch to Wiki markup when adding the following content to the page. | (+) {add-page:template=primary-type|parent=@self}Add new primary type{add-page} | {metadata-report:Name,Type,Format,Description|sort=Name|root=@self|pages=@descendents} Once the page is created, click the Add new primary type (create-page macro) to start creating a new pages. Here is an example of input to the LocalDate page. Embrace the LocalDate with square brackets [] to make the page linkable. Again switch to Wiki markup before editing. {metadata-list} || Name | [LocalDate] || || Type | Date || || Format | YYYY-MM-DD || || Description | Date in local time zone. YYYY = year, MM = month and DD = day || {metadata-list} {add-label:primary-type} The metadata-report macro will show a tabular report of all child pages.   Attributes Page The next page will act as container for all of our attributes. | (+) {add-page:template=attribute|parent=@self|title=attribute}Add new attribute{add-page} | {metadata-report:Name,Type,Format,Description|sort=Name|pages=@descendants} Here is an example of input to the startDate page. {metadata-list} || Name | [startDate] || || Type | [LocalDate] || || Format | {metadata-from:LocalDate|Format} || || Description | The projects start date || {metadata-list} {add-label:attribute} Using the metadata-from macro we fetch the text from the previously created LocalDate page. Complex Types Page The last page in this example shows how attributes can be combined together to form more complex types.   h3. Intro Overview of complex types in the domain model. | (+) {add-page:template=complex-type|parent=@self}Add a new complex type{add-page}\\ | {metadata-report:Name,Description|sort=Name|root=@self|pages=@descendents} Here is an example of input to the ProjectType page. {metadata-list} || Name | [ProjectType] || || Description | Represents a project || {metadata-list} h3. Attributes || Name || Type || Format || Description || | [projectId] | {metadata-from:projectId|Type} | {metadata-from:projectId|Format} | {metadata-from:projectId|Description} | | [name] | {metadata-from:name|Type} | {metadata-from:name|Format} | {metadata-from:name|Description} | | [description] | {metadata-from:description|Type} | {metadata-from:description|Format} | {metadata-from:description|Description} | | [startDate] | {metadata-from:startDate|Type} | {metadata-from:startDate|Format} | {metadata-from:startDate|Description} | {add-label:complex-type,entity} Gives us this Conclusion Using a web-based corporate Wiki like Confluence to create a logical domain model increases the collaboration between people with different roles in the enterprise. It’s my believe that this helps the domain model to be more accurate, and better documented. In our real project we have more pages than illustrated here to complete the documentation. We do also still use UML tools to create different types of diagrams that Confluence do not support. As a last tip, an ImageMap plugin can make those diagrams clickable when used in pages. Enjoy!

    Read the article

  • LLBLGen Pro v3.5 has been released!

    - by FransBouma
    Last weekend we released LLBLGen Pro v3.5! Below the list of what's new in this release. Of course, not everything is on this list, like the large amount of work we put in refactoring the runtime framework. The refactoring was necessary because our framework has two paradigms which are added to the framework at a different time, and from a design perspective in the wrong order (the paradigm we added first, SelfServicing, should have been built on top of Adapter, the other paradigm, which was added more than a year after the first released version). The refactoring made sure the framework re-uses more code across the two paradigms (they already shared a lot of code) and is better prepared for the future. We're not done yet, but refactoring a massive framework like ours without breaking interfaces and existing applications is ... a bit of a challenge ;) To celebrate the release of v3.5, we give every customer a 30% discount! Use the coupon code NR1ORM with your order :) The full list of what's new: Designer Rule based .NET Attribute definitions. It's now possible to specify a rule using fine-grained expressions with an attribute definition to define which elements of a given type will receive the attribute definition. Rules can be assigned to attribute definitions on the project level, to make it even easier to define attribute definitions in bulk for many elements in the project. More information... Revamped Project Settings dialog. Multiple project related properties and settings dialogs have been merged into a single dialog called Project Settings, which makes it easier to configure the various settings related to project elements. It also makes it easier to find features previously not used  by many (e.g. type conversions) More information... Home tab with Quick Start Guides. To make new users feel right at home, we added a home tab with quick start guides which guide you through four main use cases of the designer. System Type Converters. Many common conversions have been implemented by default in system type converters so users don't have to develop their own type converters anymore for these type conversions. Bulk Element Setting Manipulator. To change setting values for multiple project elements, it was a little cumbersome to do that without a lot of clicking and opening various editors. This dialog makes changing settings for multiple elements very easy. EDMX Importer. It's now possible to import entity model data information from an existing Entity Framework EDMX file. Other changes and fixes See for the full list of changes and fixes the online documentation. LLBLGen Pro Runtime Framework WCF Data Services (OData) support has been added. It's now possible to use your LLBLGen Pro runtime framework powered domain layer in a WCF Data Services application using the VS.NET tools for WCF Data Services. WCF Data Services is a Microsoft technology for .NET 4 to expose your domain model using OData. More information... New query specification and execution API: QuerySpec. QuerySpec is our new query specification and execution API as an alternative to Linq and our more low-level API. It's build, like our Linq provider, on top of our lower-level API. More information... SQL Server 2012 support. The SQL Server DQE allows paging using the new SQL Server 2012 style. More information... System Type converters. For a common set of types the LLBLGen Pro runtime framework contains built-in type conversions so you don't need to write your own type converters anymore. Public/NonPublic property support. It's now possible to mark a field / navigator as non-public which is reflected in the runtime framework as an internal/friend property instead of a public property. This way you can hide properties from the public interface of a generated class and still access it through code added to the generated code base. FULL JOIN support. It's now possible to perform FULL JOIN joins using the native query api and QuerySpec. It's left to the developer to check whether the used target database supports FULL (OUTER) JOINs. Using a FULL JOIN with entity fetches is not recommended, and should only be used when both participants in the join aren't the target of the fetch. Dependency Injection Tracing. It's now possible to enable tracing on dependency injection. Enable tracing at level '4' on the traceswitch 'ORMGeneral'. This will emit trace information about which instance of which type got an instance of type T injected into property P. Entity Instances in projections in Linq. It's now possible to return an entity instance in a custom Linq projection. It's now also possible to pass this instance to a method inside the query projection. Inheritance fully supported in this construct. Entity Framework support The Entity Framework has been updated in the recent year with code-first support and a new simpler context api: DbContext (with DbSet). The amount of code to generate is smaller and the context simpler. LLBLGen Pro v3.5 comes with support for DbContext and DbSet and generates code which utilizes these new classes. NHibernate support NHibernate v3.2+ built-in proxy factory factory support. By default the built-in ProxyFactoryFactory is selected. FluentNHibernate Session Manager uses 1.2 syntax. Fluent NHibernate mappings generate a SessionManager which uses the v1.2 syntax for the ProxyFactoryFactory location Optionally emit schema / catalog name in mappings Two settings have been added which allow the user to control whether the catalog name and/or schema name as known in the project in the designer is emitted into the mappings.

    Read the article

  • CQRS - Benefits

    - by Dylan Smith
    Thanks to all the comments and feedback from the last post I think I have a better understanding now of the benefits of CQRS (separate from the benefits of Event Sourcing). I’m going to try and sum it up here, and point out some areas where I could still use some advice: CQRS Benefits Sounds like the primary benefit of CQRS as an architecture is it allows you to create a simpler domain model by sucking out everything related to queries. I can definitely see the benefit to this, in general the domain logic related to commands is the high-value behavior in the software, but the logic required to service the queries would add a lot of low-value “noise” to the domain model that would dilute the high-value (command) behavior – sorting, paging, filtering, pre-fetch paths, etc. Also the most appropriate domain structure for implementing commands might not be the most optimal for implementing queries. To paraphrase Greg, this usually results in a domain model that is mediocre at both, piss-poor at one, or more likely piss-poor at both commands and queries. Not only will you be able to simplify your domain model by pulling out all the query logic, but at least a handful of commands in most systems will probably be “pass-though” type commands with little to no logic that just generate events. If these can be implemented directly in the command-handler and never touch the domain model, this allows you to slim down the domain model even more. Also, if you were to do event sourcing without CQRS, you no longer have a database containing the current state (only the domain model would) which makes it difficult (or impossible) to support ad-hoc querying and/or reporting that is common in most business software. Of course CQRS provides some great scalability benefits, not only scalability but I have to assume that it provides extremely low latency for most operations, especially if you have an asynchronous event bus. I know Greg says that you get a 3x scaling (Commands, Queries, Client) of your ability to perform parallel development, but IMHO, it seems like it only provides 1.5x scaling since even without CQRS you’re going to have your client loosely coupled to your domain - which is still a great benefit to be able to realize. Questions / Concerns If all the queries against an aggregate get pulled out to the Query layer, what if the only commands for that aggregate can be handled in a “pass-through” manner with the command handler directly generating events. Is it possible to have an aggregate that isn’t modeled in the domain model? Are there any issues or downsides to this? I know in the feedback from my previous posts it was suggested that having one domain model handling both commands and queries requires implementing a lot of traversals between objects that wouldn’t be necessary if it was only servicing commands. My question is, do you include traversals in your domain model based on the needs of the code, or based on the conceptual domain model? If none of my Commands require a Customer.Orders traversal, but the conceptual domain includes the concept of a set of orders belonging to a customer – should I model that in my domain model or not? I like the idea of using the Query side of the architecture as a place to put junior devs where the risk of them screwing something up has minimal impact. But I’m not sold on the idea that you can actually outsource it. Like I said in one of my comments on my previous post, the code to handle a query and generate DTO’s is going to be dead simple, but the code to process events and apply them to the tables on the query side is going to require a significant amount of domain knowledge to know which events to listen for to update each of the de-normalized tables (and what changes need to be made when each event is processed). I don’t know about everybody else, but having Indian/Russian/whatever outsourced developers have to do anything that requires significant domain knowledge has never been successful in my experience. And if you need to spec out for each new query which events to listen to and what to do with each one, well that’s probably going to be just as much work to document as it would be to just implement it. Greg made the point in a comment that doing an aggregate query like “Total Sales By Customer” is going to be inefficient if you use event sourcing but not CQRS. I don’t understand why that would be the case. I imagine in that case you’d simply have a method/property on the Customer object that calculated total sales for that customer by enumerating over the Orders collection. Then the application services layer would generate DTO’s off of the Customers collection that included say the CustomerID, CustomerName, TotalSales, or whatever the case may be. As long as you use a snapshotting implementation, I don’t see why that would be anymore inefficient in a DDD+Event Sourcing implementation than in a typical DDD implementation. Like I mentioned in my last post I still have some questions about query logic that haven’t been answered yet, but before I start asking those I want to make sure I have a strong grasp on what benefits CQRS provides.  My main concern with the query logic was that I know I could just toss it all into the query side, but I was concerned that I would be losing the benefits of using CQRS in the first place if I did that.  I want to elaborate more on this though with some example situations in an upcoming post.

    Read the article

  • How big can my SharePoint 2010 installation be?

    - by Sahil Malik
    Ad:: SharePoint 2007 Training in .NET 3.5 technologies (more information). 3 years ago, I had published “How big can my SharePoint 2007 installation be?” Well, SharePoint 2010 has significant under the covers improvements. So, how big can your SharePoint 2010 installation be? There are three kinds of limits you should know about Hard limits that cannot be exceeded by design. Configurable that are, well configurable – but the default values are set for a pretty good reason, so if you need to tweak, plan and understand before you tweak. Soft limits, you can exceed them, but it is not recommended that you do. Before you read any of the limits, read these two important disclaimers - 1. The limit depends on what you’re doing. So, don’t take the below as gospel, the reality depends on your situation. 2. There are many additional considerations in planning your SharePoint solution scalability and performance, besides just the below. So with those in mind, here goes.   Hard Limits - Zones per web app 5 RBS NAS performance Time to first byte of any response from NAS must be less than 20 milliseconds List row size 8000 bytes driven by how SP stores list items internally Max file size 2GB (default is 50MB, configurable). RBS does not increase this limit. Search metadata properties 10,000 per item crawled (pretty damn high, you’ll never need to worry about it). Max # of concurrent in-memory enterprise content types 5000 per web server, per tenant Max # of external system connections 500 per web server PerformancePoint services using Excel services as a datasource No single query can fetch more than 1 million excel cells Office Web Apps Renders One doc per second, per CPU core, per Application server, limited to a maximum of 8 cores.   Configurable Limits - Row Size Limit 6, configurable via SPWebApplication.MaxListItemRowStorage property List view lookup 8 join operations per query Max number of list items that a single operation can process at one time in normal hours 5000 Configurable via SPWebApplication.MaxItemsPerThrottledOperation   Also you get a warning at 3000, which is configurable via SPWebApplication.MaxItemsPerThrottledOperationWarningLevel   In addition, throttle overrides can be requested, throttle overrides can be disabled, and time windows can be set when throttle is disabled. Max number of list items for administrators that a single operation can process at one time in normal hours 20000 Configurable via SPWebApplication.MaxItemsPerThrottledOperationOverride Enumerating subsites 2000 Word and Powerpoint co-authoring simultaneous editors 10 (Hard limit is 99). # of webparts on a page 25 Search Crawl DBs per search service app 10 Items per crawl db 25 million Search Keywords 200 per site collection. There is a max limit of 5000, which can then be modified by editing the web.config/client.config. Concurrent # of workflows on a content db 15. Workflows running in the timer service are not counted in this limit. Further workflows are queued. Can be configured via the Set-SPFarmConfig powershell commandlet. Number of events picked by the workflow timer job and delivered to workflows 100. You can increase this limit by running additional instances of the workflow timer service. Visio services file size 50MB Visio web drawing recalculation timeout 120 seconds Configurable via – Powershell commandlet Set-SPVisioPerformance Visio services minimum and maximum cache age for data connected diagrams 0 to 24 hours. Default is 60 minutes. Configurable via – Powershell commandlet Set-SPVisioPerformance   Soft Limits - Content Databases 300 per web app Application Pools 10 per web server Managed Paths 20 per web app Content Database Size 200GB per Content DB Size of 1 site collection 100GB # of sites in a site collection 250,000 Documents in a library 30 Million, with nesting. Depends heavily on type and usage and size of documents. Items 30 million. Depends heavily on usage of items. SPGroups one SPUser can be in 5000 Users in a site collection 2 million, depends on UI, nesting, containers and underlying user store AD Principals in a SPGroup 5000 SPGroups in a site collection 10000 Search Service Instances 20 Indexed Items in Search 100 million Crawl Log entries 100 million Search Alerts 1 million per search application Search Crawled Properties 1/2 million URL removals in search 100 removals per operation User Profiles 2 million per service application Social Tags 500 million per social database Comment on the article ....

    Read the article

  • Scripting out Contained Database Users

    - by Argenis
      Today’s blog post comes from a Twitter thread on which @SQLSoldier, @sqlstudent144 and @SQLTaiob were discussing the internals of contained database users. Unless you have been living under a rock, you’ve heard about the concept of contained users within a SQL Server database (hit the link if you have not). In this article I’d like to show you that you can, indeed, script out contained database users and recreate them on another database, as either contained users or as good old fashioned logins/server principals as well. Why would this be useful? Well, because you would not need to know the password for the user in order to recreate it on another instance. I know there is a limited number of scenarios where this would be necessary, but nonetheless I figured I’d throw this blog post to show how it can be done. A more obscure use case: with the password hash (which I’m about to show you how to obtain) you could also crack the password using a utility like hashcat, as highlighted on this SQLServerCentral article. The Investigation SQL Server uses System Base Tables to save the password hashes of logins and contained database users. For logins it uses sys.sysxlgns, whereas for contained database users it leverages sys.sysowners. I’ll show you what I do to figure this stuff out: I create a login/contained user, and then I immediately browse the transaction log with, for example, fn_dblog. It’s pretty obvious that only two base tables touched by the operation are sys.sysxlgns, and also sys.sysprivs – the latter is used to track permissions. If I connect to the DAC on my instance, I can query for the password hash of this login I’ve just created. A few interesting things about this hash. This was taken on my laptop, and I happen to be running SQL Server 2014 RTM CU2, which is the latest public build of SQL Server 2014 as of time of writing. In 2008 R2 and prior versions (back to 2000), the password hashes would start with 0x0100. The reason why this changed is because starting with SQL Server 2012 password hashes are kept using a SHA512 algorithm, as opposed to SHA-1 (used since 2000) or Snefru (used in 6.5 and 7.0). SHA-1 is nowadays deemed unsafe and is very easy to crack. For regular SQL logins, this information is exposed through the sys.sql_logins catalog view, so there is really no need to connect to the DAC to grab an SID/password hash pair. For contained database users, there is (currently) no method of obtaining SID or password hashes without connecting to the DAC. If we create a contained database user, this is what we get from the transaction log: Note that the System Base Table used in this case is sys.sysowners. sys.sysprivs is used as well, and again this is to track permissions. To query sys.sysowners, you would have to connect to the DAC, as I mentioned previously. And this is what you would get: There are other ways to figure out what SQL Server uses under the hood to store contained database user password hashes, like looking at the execution plan for a query to sys.dm_db_uncontained_entities (Thanks, Robert Davis!) SIDs, Logins, Contained Users, and Why You Care…Or Not. One of the reasons behind the existence of Contained Users was the concept of portability of databases: it is really painful to maintain Server Principals (Logins) synced across most shared-nothing SQL Server HA/DR technologies (Mirroring, Availability Groups, and Log Shipping). Often times you would need the Security Identifier (SID) of these logins to match across instances, and that meant that you had to fetch whatever SID was assigned to the login on the principal instance so you could recreate it on a secondary. With contained users you normally wouldn’t care about SIDs, as the users are always available (and synced, as long as synchronization takes place) across instances. Now you might be presented some particular requirement that might specify that SIDs synced between logins on certain instances and contained database users on other databases. How would you go about creating a contained database user with a specific SID? The answer is that you can’t do it directly, but there’s a little trick that would allow you to do it. Create a login with a specified SID and password hash, create a user for that server principal on a partially contained database, then migrate that user to contained using the system stored procedure sp_user_migrate_to_contained, then drop the login. CREATE LOGIN <login_name> WITH PASSWORD = <password_hash> HASHED, SID = <sid> ; GO USE <partially_contained_db>; GO CREATE USER <user_name> FROM LOGIN <login_name>; GO EXEC sp_migrate_user_to_contained @username = <user_name>, @rename = N’keep_name’, @disablelogin = N‘disable_login’; GO DROP LOGIN <login_name>; GO Here’s how this skeleton would look like in action: And now I have a contained user with a specified SID and password hash. In my example above, I renamed the user after migrated it to contained so that it is, hopefully, easier to understand. Enjoy!

    Read the article

  • Monitoring Events in your BPEL Runtime - RSS Feeds?

    - by Ramkumar Menon
    @10g - It had been a while since I'd tried something different. so here's what I did this week!Whenever our Developers deployed processes to the BPEL runtime, or perhaps when a process gets turned off due to connectivity issues, or maybe someone retired a process, I needed to know. So here's what I did. Step 1: Downloaded Quartz libraries and went through the documentation to understand what it takes to schedule a recurring job. Step 2: Cranked out two components using Oracle JDeveloper. [Within a new Web Project] a) A simple Java Class named FeedUpdater that extends org.quartz.Job. All this class does is to connect to your BPEL Runtime [via opmn:ormi] and fetch all events that occured in the last "n" minutes. events? - If it doesn't ring a bell - its right there on the BPEL Console. If you click on "Administration > Process Log" - what you see are events.The API to retrieve the events is //get the locator reference for the domain you are interested in.Locator l = .... //Predicate to retrieve events for last "n" minutesWhereCondition wc = new WhereCondition(...) //get all those events you needed.BPELProcessEvent[] events = l.listProcessEvents(wc); After you get all these events, write out these into an RSS Feed XML structure and stream it into a file that resides either in your Apache htdocs, or wherever it can be accessed via HTTP.You can read all about RSS 2.0 here. At a high level, here is how it looks like. <?xml version = '1.0' encoding = 'UTF-8'?><rss version="2.0">  <channel>    <title>Live Updates from the Development Environment</title>    <link>http://soadev.myserver.com/feeds/</link>    <description>Live Updates from the Development Environment</description>    <lastBuildDate>Fri, 19 Nov 2010 01:03:00 PST</lastBuildDate>    <language>en-us</language>    <ttl>1</ttl>    <item>      <guid>1290213724692</guid>      <title>Process compiled</title>      <link>http://soadev.myserver.com/BPELConsole/mdm_product/administration.jsp?mode=processLog&amp;processName=&amp;dn=all&amp;eventType=all&amp;eventDate=600&amp;Filter=++Filter++</link>      <pubDate>Fri Nov 19 00:00:37 PST 2010</pubDate>      <description>SendPurchaseOrderRequestService: 3.0 Time : Fri Nov 19 00:00:37                   PST 2010</description>    </item>   ...... </channel> </rss> For writing ut XML content, read through Oracle XML Parser APIs - [search around for oracle.xml.parser.v2] b) Now that my "Job" was done, my job was half done. Next, I wrote up a simple Scheduler Servlet that schedules the above "Job" class to be executed ever "n" minutes. It is very straight forward. Here is the primary section of the code.           try {        Scheduler sched = StdSchedulerFactory.getDefaultScheduler();         //get n and make a trigger that executes every "n" seconds        Trigger trigger = TriggerUtils.makeSecondlyTrigger(n);        trigger.setName("feedTrigger" + System.currentTimeMillis());        trigger.setGroup("feedGroup");                JobDetail job = new JobDetail("SOA_Feed" + System.currentTimeMillis(), "feedGroup", FeedUpdater.class);        sched.scheduleJob(job,trigger);         }catch(Exception ex) {            ex.printStackTrace();            throw new ServletException(ex.getMessage());        } Look up the Quartz API and documentation. It will make this look much simpler.   Now that both components were ready, I packaged the Application into a war file and deployed it onto my Application Server. When the servlet initialized, the "n" second schedule was set/initialized. From then on, the servlet kept populating the RSS Feed file. I just ensured that my "Job" code keeps only 30 latest events within it, so that the feed file is small and under control. [a few kbs]   Next I opened up the feed xml on my browser - It requested a subscription - and Here I was - watching new deployments/life cycle events all popping up on my browser toolbar every 5 (actually n)  minutes!   Well, you could do it on a browser/reader of your choice - or perhaps read them like you read an email on your thunderbird!.      

    Read the article

  • ROracle support for TimesTen In-Memory Database

    - by Sam Drake
    Today's guest post comes from Jason Feldhaus, a Consulting Member of Technical Staff in the TimesTen Database organization at Oracle.  He shares with us a sample session using ROracle with the TimesTen In-Memory database.  Beginning in version 1.1-4, ROracle includes support for the Oracle Times Ten In-Memory Database, version 11.2.2. TimesTen is a relational database providing very fast and high throughput through its memory-centric architecture.  TimesTen is designed for low latency, high-volume data, and event and transaction management. A TimesTen database resides entirely in memory, so no disk I/O is required for transactions and query operations. TimesTen is used in applications requiring very fast and predictable response time, such as real-time financial services trading applications and large web applications. TimesTen can be used as the database of record or as a relational cache database to Oracle Database. ROracle provides an interface between R and the database, providing the rich functionality of the R statistical programming environment using the SQL query language. ROracle uses the OCI libraries to handle database connections, providing much better performance than standard ODBC.The latest ROracle enhancements include: Support for Oracle TimesTen In-Memory Database Support for Date-Time using R's POSIXct/POSIXlt data types RAW, BLOB and BFILE data type support Option to specify number of rows per fetch operation Option to prefetch LOB data Break support using Ctrl-C Statement caching support Times Ten 11.2.2 contains enhanced support for analytics workloads and complex queries: Analytic functions: AVG, SUM, COUNT, MAX, MIN, DENSE_RANK, RANK, ROW_NUMBER, FIRST_VALUE and LAST_VALUE Analytic clauses: OVER PARTITION BY and OVER ORDER BY Multidimensional grouping operators: Grouping clauses: GROUP BY CUBE, GROUP BY ROLLUP, GROUP BY GROUPING SETS Grouping functions: GROUP, GROUPING_ID, GROUP_ID WITH clause, which allows repeated references to a named subquery block Aggregate expressions over DISTINCT expressions General expressions that return a character string in the source or a pattern within the LIKE predicate Ability to order nulls first or last in a sort result (NULLS FIRST or NULLS LAST in the ORDER BY clause) Note: Some functionality is only available with Oracle Exalytics, refer to the TimesTen product licensing document for details. Connecting to TimesTen is easy with ROracle. Simply install and load the ROracle package and load the driver. > install.packages("ROracle") > library(ROracle) Loading required package: DBI > drv <- dbDriver("Oracle") Once the ROracle package is installed, create a database connection object and connect to a TimesTen direct driver DSN as the OS user. > conn <- dbConnect(drv, username ="", password="", dbname = "localhost/SampleDb_1122:timesten_direct") You have the option to report the server type - Oracle or TimesTen? > print (paste ("Server type =", dbGetInfo (conn)$serverType)) [1] "Server type = TimesTen IMDB" To create tables in the database using R data frame objects, use the function dbWriteTable. In the following example we write the built-in iris data frame to TimesTen. The iris data set is a small example data set containing 150 rows and 5 columns. We include it here not to highlight performance, but so users can easily run this example in their R session. > dbWriteTable (conn, "IRIS", iris, overwrite=TRUE, ora.number=FALSE) [1] TRUE Verify that the newly created IRIS table is available in the database. To list the available tables and table columns in the database, use dbListTables and dbListFields, respectively. > dbListTables (conn) [1] "IRIS" > dbListFields (conn, "IRIS") [1] "SEPAL.LENGTH" "SEPAL.WIDTH" "PETAL.LENGTH" "PETAL.WIDTH" "SPECIES" To retrieve a summary of the data from the database we need to save the results to a local object. The following call saves the results of the query as a local R object, iris.summary. The ROracle function dbGetQuery is used to execute an arbitrary SQL statement against the database. When connected to TimesTen, the SQL statement is processed completely within main memory for the fastest response time. > iris.summary <- dbGetQuery(conn, 'SELECT SPECIES, AVG ("SEPAL.LENGTH") AS AVG_SLENGTH, AVG ("SEPAL.WIDTH") AS AVG_SWIDTH, AVG ("PETAL.LENGTH") AS AVG_PLENGTH, AVG ("PETAL.WIDTH") AS AVG_PWIDTH FROM IRIS GROUP BY ROLLUP (SPECIES)') > iris.summary SPECIES AVG_SLENGTH AVG_SWIDTH AVG_PLENGTH AVG_PWIDTH 1 setosa 5.006000 3.428000 1.462 0.246000 2 versicolor 5.936000 2.770000 4.260 1.326000 3 virginica 6.588000 2.974000 5.552 2.026000 4 <NA> 5.843333 3.057333 3.758 1.199333 Finally, disconnect from the TimesTen Database. > dbCommit (conn) [1] TRUE > dbDisconnect (conn) [1] TRUE We encourage you download Oracle software for evaluation from the Oracle Technology Network. See these links for our software: Times Ten In-Memory Database,  ROracle.  As always, we welcome comments and questions on the TimesTen and  Oracle R technical forums.

    Read the article

  • ROracle support for TimesTen In-Memory Database

    - by Sherry LaMonica
    Today's guest post comes from Jason Feldhaus, a Consulting Member of Technical Staff in the TimesTen Database organization at Oracle.  He shares with us a sample session using ROracle with the TimesTen In-Memory database.  Beginning in version 1.1-4, ROracle includes support for the Oracle Times Ten In-Memory Database, version 11.2.2. TimesTen is a relational database providing very fast and high throughput through its memory-centric architecture.  TimesTen is designed for low latency, high-volume data, and event and transaction management. A TimesTen database resides entirely in memory, so no disk I/O is required for transactions and query operations. TimesTen is used in applications requiring very fast and predictable response time, such as real-time financial services trading applications and large web applications. TimesTen can be used as the database of record or as a relational cache database to Oracle Database. ROracle provides an interface between R and the database, providing the rich functionality of the R statistical programming environment using the SQL query language. ROracle uses the OCI libraries to handle database connections, providing much better performance than standard ODBC.The latest ROracle enhancements include: Support for Oracle TimesTen In-Memory Database Support for Date-Time using R's POSIXct/POSIXlt data types RAW, BLOB and BFILE data type support Option to specify number of rows per fetch operation Option to prefetch LOB data Break support using Ctrl-C Statement caching support Times Ten 11.2.2 contains enhanced support for analytics workloads and complex queries: Analytic functions: AVG, SUM, COUNT, MAX, MIN, DENSE_RANK, RANK, ROW_NUMBER, FIRST_VALUE and LAST_VALUE Analytic clauses: OVER PARTITION BY and OVER ORDER BY Multidimensional grouping operators: Grouping clauses: GROUP BY CUBE, GROUP BY ROLLUP, GROUP BY GROUPING SETS Grouping functions: GROUP, GROUPING_ID, GROUP_ID WITH clause, which allows repeated references to a named subquery block Aggregate expressions over DISTINCT expressions General expressions that return a character string in the source or a pattern within the LIKE predicate Ability to order nulls first or last in a sort result (NULLS FIRST or NULLS LAST in the ORDER BY clause) Note: Some functionality is only available with Oracle Exalytics, refer to the TimesTen product licensing document for details. Connecting to TimesTen is easy with ROracle. Simply install and load the ROracle package and load the driver. > install.packages("ROracle") > library(ROracle) Loading required package: DBI > drv <- dbDriver("Oracle") Once the ROracle package is installed, create a database connection object and connect to a TimesTen direct driver DSN as the OS user. > conn <- dbConnect(drv, username ="", password="", dbname = "localhost/SampleDb_1122:timesten_direct") You have the option to report the server type - Oracle or TimesTen? > print (paste ("Server type =", dbGetInfo (conn)$serverType)) [1] "Server type = TimesTen IMDB" To create tables in the database using R data frame objects, use the function dbWriteTable. In the following example we write the built-in iris data frame to TimesTen. The iris data set is a small example data set containing 150 rows and 5 columns. We include it here not to highlight performance, but so users can easily run this example in their R session. > dbWriteTable (conn, "IRIS", iris, overwrite=TRUE, ora.number=FALSE) [1] TRUE Verify that the newly created IRIS table is available in the database. To list the available tables and table columns in the database, use dbListTables and dbListFields, respectively. > dbListTables (conn) [1] "IRIS" > dbListFields (conn, "IRIS") [1] "SEPAL.LENGTH" "SEPAL.WIDTH" "PETAL.LENGTH" "PETAL.WIDTH" "SPECIES" To retrieve a summary of the data from the database we need to save the results to a local object. The following call saves the results of the query as a local R object, iris.summary. The ROracle function dbGetQuery is used to execute an arbitrary SQL statement against the database. When connected to TimesTen, the SQL statement is processed completely within main memory for the fastest response time. > iris.summary <- dbGetQuery(conn, 'SELECT SPECIES, AVG ("SEPAL.LENGTH") AS AVG_SLENGTH, AVG ("SEPAL.WIDTH") AS AVG_SWIDTH, AVG ("PETAL.LENGTH") AS AVG_PLENGTH, AVG ("PETAL.WIDTH") AS AVG_PWIDTH FROM IRIS GROUP BY ROLLUP (SPECIES)') > iris.summary SPECIES AVG_SLENGTH AVG_SWIDTH AVG_PLENGTH AVG_PWIDTH 1 setosa 5.006000 3.428000 1.462 0.246000 2 versicolor 5.936000 2.770000 4.260 1.326000 3 virginica 6.588000 2.974000 5.552 2.026000 4 <NA> 5.843333 3.057333 3.758 1.199333 Finally, disconnect from the TimesTen Database. > dbCommit (conn) [1] TRUE > dbDisconnect (conn) [1] TRUE We encourage you download Oracle software for evaluation from the Oracle Technology Network. See these links for our software: Times Ten In-Memory Database,  ROracle.  As always, we welcome comments and questions on the TimesTen and  Oracle R technical forums.

    Read the article

  • Access Control Service v2: Registering Web Identities in your Applications [concepts]

    - by Your DisplayName here!
    ACS v2 support two fundamental types of client identities– I like to call them “enterprise identities” (WS-*) and “web identities” (Google, LiveID, OpenId in general…). I also see two different “mind sets” when it comes to application design using the above identity types: Enterprise identities – often the fact that a client can present a token from a trusted identity provider means he is a legitimate user of the application. Trust relationships and authorization details have been negotiated out of band (often on paper). Web identities – the fact that a user can authenticate with Google et al does not necessarily mean he is a legitimate (or registered) user of an application. Typically additional steps are necessary (like filling out a form, email confirmation etc). Sometimes also a mixture of both approaches exist, for the sake of this post, I will focus on the web identity case. I got a number of questions how to implement the web identity scenario and after some conversations it turns out it is the old authentication vs. authorization problem that gets in the way. Many people use the IsAuthenticated property on IIdentity to make security decisions in their applications (or deny user=”?” in ASP.NET terms). That’s a very natural thing to do, because authentication was done inside the application and we knew exactly when the IsAuthenticated condition is true. Been there, done that. Guilty ;) The fundamental difference between these “old style” apps and federation is, that authentication is not done by the application anymore. It is done by a third party service, and in the case of web identity providers, in services that are not under our control (nor do we have a formal business relationship with these providers). Now the issue is, when you switch to ACS, and someone with a Google account authenticates, indeed IsAuthenticated is true – because that’s what he is! This does not mean, that he is also authorized to use the application. It just proves he was able to authenticate with Google. Now this obviously leads to confusion. How can we solve that? Easy answer: We have to deal with authentication and authorization separately. Job done ;) For many application types I see this general approach: Application uses ACS for authentication (maybe both enterprise and web identities, we focus on web identities but you could easily have a dual approach here) Application offers to authenticate (or sign in) via web identity accounts like LiveID, Google, Facebook etc. Application also maintains a database of its “own” users. Typically you want to store additional information about the user In such an application type it is important to have a unique identifier for your users (think the primary key of your user database). What would that be? Most web identity provider (and all the standard ACS v2 supported ones) emit a NameIdentifier claim. This is a stable ID for the client (scoped to the relying party – more on that later). Furthermore ACS emits a claims identifying the identity provider (like the original issuer concept in WIF). When you combine these two values together, you can be sure to have a unique identifier for the user, e.g.: Facebook-134952459903700\799880347 You can now check on incoming calls, if the user is already registered and if yes, swap the ACS claims with claims coming from your user database. One claims would maybe be a role like “Registered User” which can then be easily used to do authorization checks in the application. The WIF claims authentication manager is a perfect place to do the claims transformation. If the user is not registered, show a register form. Maybe you can use some claims from the identity provider to pre-fill form fields. (see here where I show how to use the Facebook API to fetch additional user properties). After successful registration (which may include other mechanisms like a confirmation email), flip the bit in your database to make the web identity a registered user. This is all very theoretical. In the next post I will show some code and provide a download link for the complete sample. More on NameIdentifier Identity providers “guarantee” that the name identifier for a given user in your application will always be the same. But different applications (in the case of ACS – different ACS namespaces) will see different name identifiers. This is by design to protect the privacy of users because identical name identifiers could be used to create “profiles” of some sort for that user. In technical terms they create the name identifier approximately like this: name identifier = Hash((Provider Internal User ID) + (Relying Party Address)) Why is this important to know? Well – when you change the name of your ACS namespace, the name identifiers will change as well and you will will lose your “connection” to your existing users. Oh an btw – never use any other claims (like email address or name) to form a unique ID – these can often be changed by users.

    Read the article

  • JPRT: A Build & Test System

    - by kto
    DRAFT A while back I did a little blogging on a system called JPRT, the hardware used and a summary on my java.net weblog. This is an update on the JPRT system. JPRT ("JDK Putback Reliablity Testing", but ignore what the letters stand for, I change what they mean every day, just to annoy people :\^) is a build and test system for the JDK, or any source base that has been configured for JPRT. As I mentioned in the above blog, JPRT is a major modification to a system called PRT that the HotSpot VM development team has been using for many years, very successfully I might add. Keeping the source base always buildable and reliable is the first step in the 12 steps of dealing with your product quality... or was the 12 steps from Alcoholics Anonymous... oh well, anyway, it's the first of many steps. ;\^) Internally when we make changes to any part of the JDK, there are certain procedures we are required to perform prior to any putback or commit of the changes. The procedures often vary from team to team, depending on many factors, such as whether native code is changed, or if the change could impact other areas of the JDK. But a common requirement is a verification that the source base with the changes (and merged with the very latest source base) will build on many of not all 8 platforms, and a full 'from scratch' build, not an incremental build, which can hide full build problems. The testing needed varies, depending on what has been changed. Anyone that was worked on a project where multiple engineers or groups are submitting changes to a shared source base knows how disruptive a 'bad commit' can be on everyone. How many times have you heard: "So And So made a bunch of changes and now I can't build!". But multiply the number of platforms by 8, and make all the platforms old and antiquated OS versions with bizarre system setup requirements and you have a pretty complicated situation (see http://download.java.net/jdk6/docs/build/README-builds.html). We don't tolerate bad commits, but our enforcement is somewhat lacking, usually it's an 'after the fact' correction. Luckily the Source Code Management system we use (another antique called TeamWare) allows for a tree of repositories and 'bad commits' are usually isolated to a small team. Punishment to date has been pretty drastic, the Queen of Hearts in 'Alice in Wonderland' said 'Off With Their Heads', well trust me, you don't want to be the engineer doing a 'bad commit' to the JDK. With JPRT, hopefully this will become a thing of the past, not that we have had many 'bad commits' to the master source base, in general the teams doing the integrations know how important their jobs are and they rarely make 'bad commits'. So for these JDK integrators, maybe what JPRT does is keep them from chewing their finger nails at night. ;\^) Over the years each of the teams have accumulated sets of machines they use for building, or they use some of the shared machines available to all of us. But the hunt for build machines is just part of the job, or has been. And although the issues with consistency of the build machines hasn't been a horrible problem, often you never know if the Solaris build machine you are using has all the right patches, or if the Linux machine has the right service pack, or if the Windows machine has it's latest updates. Hopefully the JPRT system can solve this problem. When we ship the binary JDK bits, it is SO very important that the build machines are correct, and we know how difficult it is to get them setup. Sure, if you need to debug a JDK problem that only shows up on Windows XP or Solaris 9, you'll still need to hunt down a machine, but not as a regular everyday occurance. I'm a big fan of a regular nightly build and test system, constantly verifying that a source base builds and tests out. There are many examples of automated build/tests, some that trigger on any change to the source base, some that just run every night. Some provide a protection gateway to the 'golden' source base which only gets changes that the nightly process has verified are good. The JPRT (and PRT) system is meant to guard the source base before anything is sent to it, guarding all source bases from the evil developer, well maybe 'evil' isn't the right word, I haven't met many 'evil' developers, more like 'error prone' developers. ;\^) Humm, come to think about it, I may be one from time to time. :\^{ But the point is that by spreading the build up over a set of machines, and getting the turnaround down to under an hour, it becomes realistic to completely build on all platforms and test it, on every putback. We have the technology, we can build and rebuild and rebuild, and it will be better than it was before, ha ha... Anybody remember the Six Million Dollar Man? Man, I gotta get out more often.. Anyway, now the nightly build and test can become a 'fetch the latest JPRT build bits' and start extensive testing (the testing not done by JPRT, or the platforms not tested by JPRT). Is it Open Source? No, not yet. Would you like to be? Let me know. Or is it more important that you have the ability to use such a system for JDK changes? So enough blabbering on about this JPRT system, tell me what you think. And let me know if you want to hear more about it or not. Stay tuned for the next episode, same Bloody Bat time, same Bloody Bat channel. ;\^) -kto

    Read the article

  • Web Services Example - Part 2: Programmatic

    - by Denis T
    In this edition of the ADF Mobile blog we'll tackle part 2 of our Web Service examples.  In this posting we'll take a look at using a SOAP Web Service but calling it programmatically in code and parsing the return into a bean. Getting the sample code: Just click here to download a zip of the entire project.  You can unzip it and load it into JDeveloper and deploy it either to iOS or Android.  Please follow the previous blog posts if you need help getting JDeveloper or ADF Mobile installed.  Note: This is a different workspace than WS-Part1 Defining our Web Service: Just like our first installment, we are using the same public weather forecast web service provided free by CDYNE Corporation.  Sometimes this service goes down so please ensure you know it's up before reporting this example isn't working. We're going to concentrate on the same two web service methods, GetCityForecastByZIP and GetWeatherInformation. Defing the Application: The application setup is identical to the Weather1 version.  There are some improvements to the data that is displayed as part of this example though.  Now we are able to show the associated image along with each forecast line when using the Forecast By Zip feature.  We've also added the temperature Hi/Low values into the UI. Summary of Fundamental Changes In This Application The most fundamental change is that we're binding the UI to the Bean Data Controls instead of directly to the Web Service Data Controls.  This gives us much more flexibility to control the shape of the data and allows us to do caching of the data outside of the Web Service.  This way if your application is, say offline, your bean could still populate with data from a local cache and still show you some UI as opposed to completely failing because you don't have any connectivity. In general we promote this type of programming technique with ADF Mobile to insulate your application from any issues with network connectivity. What's different with this example? We have setup the Web Service DC the same way but now we have managed beans to process the data.  The following classes define the "Model" of our application:  CityInformation-CityForecast-Forecast, WeatherInformation-WeatherDescription.  We use WeatherBean for UI interaction to the model layer.  If you look through this example, we don't really do that much with the java code except use it to grab the image URL from the weather description.  In a more realistic example, you might be using some JDBC classes to persist the data to a local database. To have a good architecture it is always good to keep your model and UI layers separate.  This gets muddied if you start to use bindings on a page invoked from Java code and this java code starts to become your "model" layer.  Since bindings are page specific, your model layer starts to become entwined with your UI.  Not good!  To help with this, we've added some utility functions that let you invoke DC methods without having a binding and thus execute methods from your "model" layer without requiring a binding in your page definition.  We do this with the invokeDataControlMethod of the AdfmfJavaUtilities class.  An example of this method call is available in line 95 of WeatherInformation.java and line 93 of CityInformation.Java. What's a GenericType? Because Web Service Data Controls (and also URL Data Controls AKA REST) use generic name/value pairs to define their structure and don't have strongly typed objects, these are actually stored internally as GenericType objects.  The GenericType class is simply a property map of name/value pairs that can be hierarchical.  There are methods like getAttribute where you supply the index of the attribute or it's string property name.  Why is this important to know?  Because invokeDataControlMethod returns GenericType objects and developers either need to parse these GenericType objects themselves or use one of our helper functions. GenericTypeBeanSerializationHelper This class does exactly what it's name implies.  It's a helper class for developers to aid in serialization of GenericTypes to/from java objects.  This is extremely handy if you have a large GenericType object with many attributes (or you're just lazy like me!) and you just want to parse it out into a real java object you can use more easily.  Here you would use the fromGenericType method.  This method takes the class of the Java object you wish to return and the GenericType as parameters.  The method then parses through each attribute in the GenericType and uses reflection to set that same attribute in the Java class.  Then the method returns that new object of the class you specified.  This is obviously very handy to avoid a lot of shuffling code between GenericType and your own Java classes.  The reverse method, toGenericType is also available when you want to go the other way.  In this case you supply the string that represents the package location in the DataControl definition (Example: "MyDC.myParams.MyCollection") and then pass in the Java object you have that holds the data and a GenericType is returned to you.  Again, it will use reflection to calculate the attributes that match between the java class and the GenericType and call the getters/setters on those. Issues and Possible Improvements: In the next installment we'll show you how to make your web service calls asynchronously so your UI will fill dynamically when the service call returns but in the meantime you show the data you have locally in your bean fed from some local cache.  This gives your users instant delivery of some data while you fetch other data in the background.

    Read the article

  • SQL Server - Rebuilding Indexes

    - by Renso
    Goal: Rebuild indexes in SQL server. This can be done one at a time or with the example script below to rebuild all index for a specified table or for all tables in a given database. Why? The data in indexes gets fragmented over time. That means that as the index grows, the newly added rows to the index are physically stored in other sections of the allocated database storage space. Kind of like when you load your Christmas shopping into the trunk of your car and it is full you continue to load some on the back seat, in the same way some storage buffer is created for your index but once that runs out the data is then stored in other storage space and your data in your index is no longer stored in contiguous physical pages. To access the index the database manager has to "string together" disparate fragments to create the full-index and create one contiguous set of pages for that index. Defragmentation fixes that. What does the fragmentation affect?Depending of course on how large the table is and how fragmented the data is, can cause SQL Server to perform unnecessary data reads, slowing down SQL Server’s performance.Which index to rebuild?As a rule consider that when reorganize a table's clustered index, all other non-clustered indexes on that same table will automatically be rebuilt. A table can only have one clustered index.How to rebuild all the index for one table:The DBCC DBREINDEX command will not automatically rebuild all of the indexes on a given table in a databaseHow to rebuild all indexes for all tables in a given database:USE [myDB]    -- enter your database name hereDECLARE @tableName varchar(255)DECLARE TableCursor CURSOR FORSELECT table_name FROM information_schema.tablesWHERE table_type = 'base table'OPEN TableCursorFETCH NEXT FROM TableCursor INTO @tableNameWHILE @@FETCH_STATUS = 0BEGINDBCC DBREINDEX(@tableName,' ',90)     --a fill factor of 90%FETCH NEXT FROM TableCursor INTO @tableNameENDCLOSE TableCursorDEALLOCATE TableCursorWhat does this script do?Reindexes all indexes in all tables of the given database. Each index is filled with a fill factor of 90%. While the command DBCC DBREINDEX runs and rebuilds the indexes, that the table becomes unavailable for use by your users temporarily until the rebuild has completed, so don't do this during production  hours as it will create a shared lock on the tables, although it will allow for read-only uncommitted data reads; i.e.e SELECT.What is the fill factor?Is the percentage of space on each index page for storing data when the index is created or rebuilt. It replaces the fill factor when the index was created, becoming the new default for the index and for any other nonclustered indexes rebuilt because a clustered index is rebuilt. When fillfactor is 0, DBCC DBREINDEX uses the fill factor value last specified for the index. This value is stored in the sys.indexes catalog view. If fillfactor is specified, table_name and index_name must be specified. If fillfactor is not specified, the default fill factor, 100, is used.How do I determine the level of fragmentation?Run the DBCC SHOWCONTIG command. However this requires you to specify the ID of both the table and index being. To make it a lot easier by only requiring you to specify the table name and/or index you can run this script:DECLARE@ID int,@IndexID int,@IndexName varchar(128)--Specify the table and index namesSELECT @IndexName = ‘index_name’    --name of the indexSET @ID = OBJECT_ID(‘table_name’)  -- name of the tableSELECT @IndexID = IndIDFROM sysindexesWHERE id = @ID AND name = @IndexName--Show the level of fragmentationDBCC SHOWCONTIG (@id, @IndexID)Here is an example:DBCC SHOWCONTIG scanning 'Tickets' table...Table: 'Tickets' (1829581556); index ID: 1, database ID: 13TABLE level scan performed.- Pages Scanned................................: 915- Extents Scanned..............................: 119- Extent Switches..............................: 281- Avg. Pages per Extent........................: 7.7- Scan Density [Best Count:Actual Count].......: 40.78% [115:282]- Logical Scan Fragmentation ..................: 16.28%- Extent Scan Fragmentation ...................: 99.16%- Avg. Bytes Free per Page.....................: 2457.0- Avg. Page Density (full).....................: 69.64%DBCC execution completed. If DBCC printed error messages, contact your system administrator.What's important here?The Scan Density; Ideally it should be 100%. As time goes by it drops as fragmentation occurs. When the level drops below 75%, you should consider re-indexing.Here are the results of the same table and clustered index after running the script:DBCC SHOWCONTIG scanning 'Tickets' table...Table: 'Tickets' (1829581556); index ID: 1, database ID: 13TABLE level scan performed.- Pages Scanned................................: 692- Extents Scanned..............................: 87- Extent Switches..............................: 86- Avg. Pages per Extent........................: 8.0- Scan Density [Best Count:Actual Count].......: 100.00% [87:87]- Logical Scan Fragmentation ..................: 0.00%- Extent Scan Fragmentation ...................: 22.99%- Avg. Bytes Free per Page.....................: 639.8- Avg. Page Density (full).....................: 92.10%DBCC execution completed. If DBCC printed error messages, contact your system administrator.What's different?The Scan Density has increased from 40.78% to 100%; no fragmentation on the clustered index. Note that since we rebuilt the clustered index, all other index were also rebuilt.

    Read the article

  • BIP 11g Dynamic SQL

    - by Tim Dexter
    Back in the 10g release, if you wanted something beyond the standard query for your report extract; you needed to break out your favorite text editor. You gotta love 'vi' and hate emacs, am I right? And get to building a data template, they were/are lovely to write, such fun ... not! Its not fun writing them by hand but, you do get to do some cool stuff around the data extract including dynamic SQL. By that I mean the ability to add content dynamically to your your query at runtime. With 11g, we spoiled you with a visual builder, no more vi or notepad sessions, a friendly drag and drop interface allowing you to build hierarchical data sets, calculated columns, summary columns, etc. You can still create the dynamic SQL statements, its not so well documented right now, in lieu of doc updates here's the skinny. If you check out the 10g process to create dynamic sql in the docs. You need to create a data trigger function where you assign the dynamic sql to a global variable that's matched in your report SQL. In 11g, the process is really the same, BI Publisher just provides a bit more help to define what trigger code needs to be called. You still need to create the function and place it inside a package in the db. Here's a simple plsql package with the 'beforedata' function trigger. Spec create or replace PACKAGE BIREPORTS AS whereCols varchar2(2000); FUNCTION beforeReportTrig return boolean; end BIREPORTS; Body create or replace PACKAGE BODY BIREPORTS AS   FUNCTION beforeReportTrig return boolean AS   BEGIN       whereCols := ' and d.department_id = 100';     RETURN true;   END beforeReportTrig; END BIREPORTS; you'll notice the additional where clause (whereCols - declared as a public variable) is hard coded. I'll cover parameterizing that in my next post. If you can not wait, check the 10g docs for an example. I have my package compiling successfully in the db. Now, onto the BIP data model definition. 1. Create a new data model and go ahead and create your query(s) as you would normally. 2. In the query dialog box, add in the variables you want replaced at runtime using an ampersand rather than a colon e.g. &whereCols.   select     d.DEPARTMENT_NAME, ...  from    "OE"."EMPLOYEES" e,     "OE"."DEPARTMENTS" d  where   d."DEPARTMENT_ID"= e."DEPARTMENT_ID" &whereCols   Note that 'whereCols' matches the global variable name in our package. When you click OK to clear the dialog, you'll be asked for a default value for the variable, just use ' and 1=1' That leading space is important to keep the SQL valid ie required whitespace. This value will be used for the where clause if case its not set by the function code. 3. Now click on the Event Triggers tree node and create a new trigger of the type Before Data. Type in the default package name, in my example, 'BIREPORTS'. Then hit the update button to get BIP to fetch the valid functions.In my case I get to see the following: Select the BEFOREREPORTTRIG function (or your name) and shuttle it across. 4. Save your data model and now test it. For now, you can update the where clause via the plsql package. Next time ... parametrizing the dynamic clause.

    Read the article

  • Objective-C NSMutableArray Count Causes EXC_BAD_ACCESS

    - by JoshEH
    I've been stuck on this for days and each time I come back to it I keep making my code more and more confusing to myself, lol. Here's what I'm trying to do. I have table list of charges, I tap on one and brings up a model view with charge details. Now when the model is presented a object is created to fetch a XML list of users and parses it and returns a NSMutableArray via a custom delegate. I then have a button that presents a picker popover, when the popover view is called the user array is used in an initWithArray call to the popover view. I know the data in the array is right, but when [pickerUsers count] is called I get an EXC_BAD_ACCESS. I assume it's a memory/ownership issue but nothing seems to help. Any help would be appreciated. Relevant code snippets: Charge Popover (Charge details model view): @interface ChargePopoverViewController ..... NSMutableArray *pickerUserList; @property (nonatomic, retain) NSMutableArray *pickerUserList; @implementation ChargePopoverViewController @synthesize whoOwesPickerButton, pickerUserList; - (void)viewDidLoad { JEHWebAPIPickerUsers *fetcher = [[JEHWebAPIPickerUsers alloc] init]; fetcher.delegate = self; [fetcher fetchUsers]; } -(void) JEHWebAPIFetchedUsers:(NSMutableArray *)theData { [pickerUserList release]; pickerUserList = theData; } - (void) pickWhoPaid: (id) sender { UserPickerViewController* content = [[UserPickerViewController alloc] initWithArray:pickerUserList]; UIPopoverController *popover = [[UIPopoverController alloc] initWithContentViewController:content]; [popover presentPopoverFromRect:whoPaidPickerButton.frame inView:self.view permittedArrowDirections:UIPopoverArrowDirectionAny animated:YES]; content.delegate = self; } User Picker View Controller @interface UserPickerViewController ..... NSMutableArray *pickerUsers; @property(nonatomic, retain) NSMutableArray *pickerUsers; @implementation UserPickerViewController @synthesize pickerUsers; -(UserPickerViewController*) initWithArray:(NSMutableArray *)theUsers { self = [super init]; if ( self ) { self.pickerUsers = theUsers; } return self; } - (NSInteger)pickerView:(UIPickerView *)thePickerView numberOfRowsInComponent:(NSInteger)component { // Dies Here EXC_BAD_ACCESS, but NSLog(@"The content of array is%@",pickerUsers); shows correct array data return [pickerUsers count]; } I can provide additional code if it might help. Thanks in advance.

    Read the article

  • One-to-one Mapping issue with NHibernate/Fluent: Foreign Key not updateing

    - by Trevor
    Summary: Parent and Child class. One to one relationship between the Parent and Child. Parent has a FK property which references the primary key of the Child. Code as follows: public class NHTestParent { public virtual Guid NHTestParentId { get; set; } public virtual Guid ChildId { get { return ChildRef.NHTestChildId; } set { } } public virtual string ParentName { get; set; } protected NHTestChild _childRef; public virtual NHTestChild ChildRef { get { if (_childRef == null) _childRef = new NHTestChild(); return _childRef; } set { _childRef = value; } } } public class NHTestChild { public virtual Guid NHTestChildId { get; set; } public virtual string ChildName { get; set; } } With the following Fluent mappings: Parent Mapping Id(x => x.NHTestParentId); Map(x => x.ParentName); Map(x => x.ChildId); References(x => x.ChildRef, "ChildId").Cascade.All(); Child Mapping: Id(x => x.NHTestChildId); Map(x => x.ChildName); If I do something like (pseudo code) ... HTestParent parent = new NHTestParent(); parent.ParentName = "Parent 1"; parent.ChildRef.ChildName = "Child 1"; nhibernateSession.SaveOrUpdate(aParent); Commit; ... I get an error: "Invalid index 3 for this SqlParameterCollection with Count=3" If I change the parent 'References' line as follows (i.e. provide the name of the child property I'm pointing at): References(x => x.ChildRef, "ChildId").PropertyRef("NHTestChildId").Cascade.All(); I get the error: "Unable to resolve property: NHTestChildId" So, I tried the 'HasOne()' reference setting, as follows: HasOne<NHTestChild>(x => x.ChildRef).ForeignKey("ChildId").Cascade.All().Fetch.Join(); This results in the save working, but the load fails to find the child. If I inspect the SQL Nhibernate produces I can see that NHibernate is assuming the Primary key of the parent is the link to the child (i.e. load join condition is "parent.NHTestParentId = child.NHTestChildId). The 'ForeignKey' specified appears to be ignored. I can set any value and no error occurs - the join just always fails and no child is returned. I've tried a number of slight variations on the above. It seems like it should be a simple thing to achieve. Any ideas?

    Read the article

  • Playing an InputStream video in Blackberry JDE.

    - by Jenny
    I think I'm using InputStream incorrectly with a Blackberry 9000 simulator: I found some sample code, http://www.blackberry.com/knowledgecenterpublic/livelink.exe/fetch/2000/348583/800332/1089414/How%5FTo%5F-%5FPlay%5Fvideo%5Fwithin%5Fa%5FBlackBerry%5Fsmartphone%5Fapplication.html?nodeid=1383173&vernum=0 that lets you play video from within a Blackberry App. The code claims it can handle HTTP, but it's taken some fandangling to get it to actually approach doing so: http://pastie.org/609491 Specifically, I'm doing: StreamConnection s = null; s = (StreamConnection)Connector.open("http://10.252.9.15/eggs.3gp"); HttpConnection c = (HttpConnection)s; InputStream i = c.openInputStream(); System.out.println("~~~~~I have a connection?~~~~~~" + c); System.out.println("~~~~~I have a URL?~~~~" + c.getURL()); System.out.println("~~~~~I have a type?~~~~" + c.getType()); System.out.println("~~~~~I have a status?~~~~~~" + c.getResponseCode()); System.out.println("~~~~~I have a stream?~~~~~~" + i); player = Manager.createPlayer(i, c.getType()); I've found that this is the only way I can get an InputStream from an HTTPConnection without causing a: "JUM Error 104: Uncaught NullPointer Exception". (That is, the casting as a StreamConnection, and THEN as an HttpConnection stops it from crashing). However, I'm still not streaming video. Before, a stream wasn't able to be created (it would crash with the null pointer exception). Now, a stream is being made, the debugger claims it's begining to stream video from it...and nothing happens. No video plays. The app doesn't freeze, or crash or anything. I can 'pause' and 'play' freely, and get appropriate debug messages for both. But no video shows up. If I'm playing a video stored locally on the blackberry, everything is fine (it actually plays the video), so I know the Player itself is working fine, I"m just wondering if maybe I have something wrong with my stream? The API says the player can take in an InputStream. Is there a specific kind it needs? How can I query my inputstream to know if it's valid? It existing is further than I've gotten before. -Jenny Edit: I'm on a Blackberry Bold simulator (9000). I've heard that some versions of phones do NOT stream video via HTTP, however, the Bold does. I have yet to see examples of this though. When I go to the internet and point at a blackberry playable video, it attempts to stream, and then asks me to physically download the file (and then plays fine once I download). Edit: Also, I have a physical blackberry Bold, as well, but it can't stream either (I've gone to m.youtube.com, only to get a server/content not found error). Is there something special I need to do to stream RTSP content?

    Read the article

  • Core Data NSPredicate for relationships.

    - by Mugunth Kumar
    My object graph is simple. I've a feedentry object that stores info about RSS feeds and a relationship called Tag that links to "TagValues" object. Both the relation (to and inverse) are to-many. i.e, a feed can have multiple tags and a tag can be associated to multiple feeds. I referred to http://stackoverflow.com/questions/844162/how-to-do-core-data-queries-through-a-relationship and created a NSFetchRequest. But when fetch data, I get an exception stating, NSInvalidArgumentException unimplemented SQL generation for predicate What should I do? I'm a newbie to core data :( I know I've done something terribly wrong... Please help... Thanks -- NSFetchRequest *fetchRequest = [[NSFetchRequest alloc] init]; // Edit the entity name as appropriate. NSEntityDescription *entity = [NSEntityDescription entityForName:@"FeedEntry" inManagedObjectContext:managedObjectContext]; [fetchRequest setEntity:entity]; // Edit the sort key as appropriate. NSSortDescriptor *sortDescriptor = [[NSSortDescriptor alloc] initWithKey:@"authorname" ascending:NO]; NSArray *sortDescriptors = [[NSArray alloc] initWithObjects:sortDescriptor, nil]; [fetchRequest setSortDescriptors:sortDescriptors]; NSEntityDescription *tagEntity = [NSEntityDescription entityForName:@"TagValues" inManagedObjectContext:self.managedObjectContext]; NSPredicate *tagPredicate = [NSPredicate predicateWithFormat:@"tagName LIKE[c] 'nyt'"]; NSFetchRequest *tagRequest = [[NSFetchRequest alloc] init]; [tagRequest setEntity:tagEntity]; [tagRequest setPredicate:tagPredicate]; NSError *error = nil; NSArray* predicates = [self.managedObjectContext executeFetchRequest:tagRequest error:&error]; TagValues *tv = (TagValues*) [predicates objectAtIndex:0]; NSLog(tv.tagName); // it is nyt here... NSPredicate *predicate = [NSPredicate predicateWithFormat:@"tag IN %@", predicates]; [fetchRequest setPredicate:predicate]; // Edit the section name key path and cache name if appropriate. // nil for section name key path means "no sections". NSFetchedResultsController *aFetchedResultsController = [[NSFetchedResultsController alloc] initWithFetchRequest:fetchRequest managedObjectContext:managedObjectContext sectionNameKeyPath:nil cacheName:@"Root"]; aFetchedResultsController.delegate = self; self.fetchedResultsController = aFetchedResultsController; --

    Read the article

< Previous Page | 92 93 94 95 96 97 98 99 100 101 102 103  | Next Page >