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  • New harddrives failing within weeks.

    - by Jason Kealey
    I've experienced 8 hard disk failures in 3 months and have tried many things to solve the issue permanently but I have failed. I would like to know if you have any advice for me. System was running Win XP on an Asus P5W-DH Deluxe. I have setup a RAID-1 array. I started out with 2 x 500 GB 7200RPM Western Digital drives. One died. I took it out to RMA it. On the same day, the router was fried. Assumed a power surge occurred; connected an older UPS to protect the system. Once I got my hands on an identical disk, I installed it. The RAID array was rebuilt. A few days later, the other one died. Assumed the rebuild caused it to fail. Took it out for RMA. Before the other one arrived, the remaining one died. I then discovered I could re-enable them using the Intel Matrix Storage Manager. I re-enabled both and the system seemed fine for a week, until both died again. I got two new 1.5 TB 7200RPM Seagate drives and re-installed Windows 7. Also replaced the UPS and power supply. They both died again. The voltage on the plug is stable between 120 and 122V as per the UPS. None of the other devices have had any problems (monitors, etc.). At this point, I see two options: a) electrical issue in the house that was, for some reason, not blocked by the UPS. b) something else inside the system causing surges? motherboard? onboard raid controller? Failures happen fairly quickly, between 2 and 14 days after I fix the previous issue. I just gotten a new computer (Core i7) to replace it. If it is stable, I can determine that b) was the problem. If it fries its hard drive again, I can determine that it is an electrical issue in the house. Do you have any other thoughts? Any tools I can run on the drives that failed to get more information about the original SMART event history?

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  • MongoDB and datasets that don't fit in RAM no matter how hard you shove

    - by sysadmin1138
    This is very system dependent, but chances are near certain we'll scale past some arbitrary cliff and get into Real Trouble. I'm curious what kind of rules-of-thumb exist for a good RAM to Disk-space ratio. We're planning our next round of systems, and need to make some choices regarding RAM, SSDs, and how much of each the new nodes will get. But now for some performance details! During normal workflow of a single project-run, MongoDB is hit with a very high percentage of writes (70-80%). Once the second stage of the processing pipeline hits, it's extremely high read as it needs to deduplicate records identified in the first half of processing. This is the workflow for which "keep your working set in RAM" is made for, and we're designing around that assumption. The entire dataset is continually hit with random queries from end-user derived sources; though the frequency is irregular, the size is usually pretty small (groups of 10 documents). Since this is user-facing, the replies need to be under the "bored-now" threshold of 3 seconds. This access pattern is much less likely to be in cache, so will be very likely to incur disk hits. A secondary processing workflow is high read of previous processing runs that may be days, weeks, or even months old, and is run infrequently but still needs to be zippy. Up to 100% of the documents in the previous processing run will be accessed. No amount of cache-warming can help with this, I suspect. Finished document sizes vary widely, but the median size is about 8K. The high-read portion of the normal project processing strongly suggests the use of Replicas to help distribute the Read traffic. I have read elsewhere that a 1:10 RAM-GB to HD-GB is a good rule-of-thumb for slow disks, As we are seriously considering using much faster SSDs, I'd like to know if there is a similar rule of thumb for fast disks. I know we're using Mongo in a way where cache-everything really isn't going to fly, which is why I'm looking at ways to engineer a system that can survive such usage. The entire dataset will likely be most of a TB within half a year and keep growing.

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  • Need help recovering a corrupt SQL database

    - by user570079
    I have a very special case that I have been working on for several days. I have a very large SQL Server 2008 database (about 2 TB) that contains 500 filegroups to support very large partitioned tables. Recently we had a catastophic failure on one of the drive and lost several filegroups and the database became in-accessible. We have been doing filegroup backups on a daily basis, but due to other issues, we lost our most recent backup of the log and the primary filegroup. We have all the data backed up but the primary filegroup backup is old. There have been no schema changes since the primary filegroup backup, but the lsn's are now all out of sync and we cannot recover the data. I have tried everything I could think of (and have tried just about every trick and hack I could google) but I still end up at the same point where I get messages saying that the files for filegroup x do not match the primary filegroup. I am now at the point of trying to edit the system tables (we have a separate temporary environment to do this so we are not worried about corrupting any production databases). I have tried updated sys.sysdbreg, sys.sysbrickfiles, and sys.sysprufiles to try to trick SQL into thinking all the files are online, but a "Select * From OPENROWSET(TABLE DBPROP, 5)" shows a different database state from what I see in sys.sysdbreg. I am now thinking I need to somehow edit the headers of the actual data files to try to line up the lsn's with the primary. I appreciate any help anyone can give me here, but please do not respond with things like "you are not supposed to do edit mdf, ndf files...." or "see msdn article....", etc. This is an advanced emergency case and I need a real hack so we can just get to the data in this corrupt database and export to a fresh new database. I know there is a way to do this, but not knowing what the DBPROP system functions does (i.e. does it look at system tables or does it actually open the file) is keeping me from trying to figure out how to fool SQL into allowing me to read these files. Thanks for any help.

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  • My new hard drive doesn't have rights on my old one?

    - by Allan
    Until recently I had a 1 TB hard disk with Windows 7 on it, I have bought myself a SSD, removed the old harddisc and installed Windows 7 on my new one. After that I put back the old hard disk, and formatted it, now I could use that as backup and to keep files on. Nice, right? Well I was updating .Net framework through Windows update, when it stalled. I noticed some space was used on one of the drives on my secondary 'previously primary' hard disk. Apparently it was the .Net framework, trying to save some temporary files on my secondary disc, because it was the one with the most space. It was like it didn't get access. I cancled the installation and rebooted the computer. Now wanting to remove the temporary folder on my secondary harddisk. It told me. "You don't have access by SYSTEM", I don't understand, my user is administrator, its the only user there is and at the same time I can remove and delete any other folder on that drive. I'm gonna go a little pseudo here. But it feels as if the computer treats the old harddisk as protected from tampering by the new SSD. Also, I feel I should mention, they are both listed as primary, ... primary 0 and primary 1. Both using SATA cable. My old hard drive was partioned into 3 drives. 2 of them said the current owner was 'Administrator/myPCname' and the third one said the current owner was 'SYSTEM' I changed them all into the only one that I could pick from the list, which is my user since the 'Administrators/myPCname' wasn't exactly wrong.. could it be that they were somehow still attached to the old OS?.. the fact is I named my computer the exact same thing as it was called before installing a new windows.. so I can't really tell if its an old ownership or not. Also.. I'm currently logged in as 'myname' and I'm administrator.. now trying to delete the previously mentioned files.. it says 'you need access from 'myname' – and it can't delete.. That seems really messed up, I mean I'm logged in as the name it wants me to use. Is there maybe someway I could reset all the users on my computer? Or create some default? I don't know – I just want it to take a form I have always known, from a standard Windows point of view.

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  • Computer randomly reboots during "intensive activity".

    - by Reznor
    My friend has been playing games on his new build for some time now. However, lately, his computer will randomly reboot out of nowhere, so far only happening in game, and presumably only to happen in game as it happens nowhere else. This can happen in game during play or even in the options. Note, it isn't a crash or blue screen. It's just a normal reboot. This started today, I believe, and has only occured in two games: Dead Space and Stalker: Shadow of Chernobyl. He has played a handful of games before these, for about a week or so, without this problem. We theorized on two possibilities: Maybe something is overheating? Maybe the power supply is inadequate? These two were quickly dismissed, as all his components were operating at normal temperatures when he got back to his desktop from the reboot, and we all know these parts don't exactly cool down quickly, especially if they get hot enough to trigger a reboot. Besides, I know at-least my motherboard reports processor overheating at start-up, and requests I press f1 to continue into boot. The PSU one was dismissed too. He has an 850w power supply on a rig that was estimated to take only 720 some watts, that's with some overcompensating to be safe. He opened up his case to make sure nothing was seated wrong or in the way. All was fine, but he did notice a sticker on his video card. It had a giant barcode on it and some numbers. Now, I'm used to seeing these stickers, they're the warranty stickers, right, and removal voids the warranty? Yeah, well, we find it odd because this sticker is slapped right over the circuits of the video card, not on a block or anything. Is this normal? Should he remove it? Right now, I am concerned with the memory. Could that be at fault? Here are his specs: Windows 7 Home Premium, 64-Bit Intel i7 950 EVGA GeForce 570 GTX 4 GB DDR3 PC10666 dual-channel Corsair RAM Corsair 850w PSU Gigabyte GA-X58A-UD3R Western Digital 1 TB WD1001FALS

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  • 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(); } ... }

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  • No, iCloud Isn’t Backing Them All Up: How to Manage Photos on Your iPhone or iPad

    - by Chris Hoffman
    Are the photos you take with your iPhone or iPad backed up in case you lose your device? If you’re just relying on iCloud to manage your important memories, your photos may not be backed up at all. Apple’s iCloud has a photo-syncing feature in the form of “Photo Stream,” but Photo Stream doesn’t actually perform any long-term backups of your photos. iCloud’s Photo Backup Limitations Assuming you’ve set up iCloud on your iPhone or iPad, your device is using a feature called “Photo Stream” to automatically upload the photos you take to your iCloud storage and sync them across your devices. Unfortunately, there are some big limitations here. 1000 Photos: Photo Stream only backs up the latest 1000 photos. Do you have 1500 photos in your Camera Roll folder on your phone? If so, only the latest 1000 photos are stored in your iCloud account online. If you don’t have those photos backed up elsewhere, you’ll lose them when you lose your phone. If you have 1000 photos and take one more, the oldest photo will be removed from your iCloud Photo Stream. 30 Days: Apple also states that photos in your Photo Stream will be automatically deleted after 30 days “to give your devices plenty of time to connect and download them.” Some people report photos aren’t deleted after 30 days, but it’s clear you shouldn’t rely on iCloud for more than 30 days of storage. iCloud Storage Limits: Apple only gives you 5 GB of iCloud storage space for free, and this is shared between backups, documents, and all other iCloud data. This 5 GB can fill up pretty quickly. If your iCloud storage is full and you haven’t purchased any more storage more from Apple, your photos aren’t being backed up. Videos Aren’t Included: Photo Stream doesn’t include videos, so any videos you take aren’t automatically backed up. It’s clear that iCloud’s Photo Stream isn’t designed as a long-term way to store your photos, just a convenient way to access recent photos on all your devices before you back them up for real. iCloud’s Photo Stream is Designed for Desktop Backups If you have a Mac, you can launch iPhoto and enable the Automatic Import option under Photo Stream in its preferences pane. Assuming your Mac is on and connected to the Internet, iPhoto will automatically download photos from your photo stream and make local backups of them on your hard drive. You’ll then have to back up your photos manually so you don’t lose them if your Mac’s hard drive ever fails. If you have a Windows PC, you can install the iCloud Control Panel, which will create a Photo Stream folder on your PC. Your photos will be automatically downloaded to this folder and stored in it. You’ll want to back up your photos so you don’t lose them if your PC’s hard drive ever fails. Photo Stream is clearly designed to be used along with a desktop application. Photo Stream temporarily backs up your photos to iCloud so iPhoto or iCloud Control Panel can download them to your Mac or PC and make a local backup before they’re deleted. You could also use iTunes to sync your photos from your device to your PC or Mac, but we don’t really recommend it — you should never have to use iTunes. How to Actually Back Up All Your Photos Online So Photo Stream is actually pretty inconvenient — or, at least, it’s just a way to temporarily sync photos between your devices without storing them long-term. But what if you actually want to automatically back up your photos online without them being deleted automatically? The solution here is a third-party app that does this for you, offering the automatic photo uploads with long-term storage. There are several good services with apps in the App Store: Dropbox: Dropbox’s Camera Upload feature allows you to automatically upload the photos — and videos — you take to your Dropbox account. They’ll be easily accessible anywhere there’s a Dropbox app and you can get much more free Dropbox storage than you can iCloud storage. Dropbox will never automatically delete your old photos. Google+: Google+ offers photo and video backups with its Auto Upload feature, too. Photos will be stored in your Google+ Photos — formerly Picasa Web Albums — and will be marked as private by default so no one else can view them. Full-size photos will count against your free 15 GB of Google account storage space, but you can also choose to upload an unlimited amount of photos at a smaller resolution. Flickr: The Flickr app is no longer a mess. Flickr offers an Auto Upload feature for uploading full-size photos you take and free Flickr accounts offer a massive 1 TB of storage for you to store your photos. The massive amount of free storage alone makes Flickr worth a look. Use any of these services and you’ll get an online, automatic photo backup solution you can rely on. You’ll get a good chunk of free space, your photos will never be automatically deleted, and you can easily access them from any device. You won’t have to worry about storing local copies of your photos and backing them up manually. Apple should fix this mess and offer a better solution for long-term photo backup, especially considering the limitations aren’t immediately obvious to users. Until they do, third-party apps are ready to step in and take their place. You can also automatically back up your photos to the web on Android with Google+’s Auto Upload or Dropbox’s Camera Upload. Image Credit: Simon Yeo on Flickr     

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  • Azure &ndash; Part 6 &ndash; Blob Storage Service

    - by Shaun
    When migrate your application onto the Azure one of the biggest concern would be the external files. In the original way we understood and ensure which machine and folder our application (website or web service) is located in. So that we can use the MapPath or some other methods to read and write the external files for example the images, text files or the xml files, etc. But things have been changed when we deploy them on Azure. Azure is not a server, or a single machine, it’s a set of virtual server machine running under the Azure OS. And even worse, your application might be moved between thses machines. So it’s impossible to read or write the external files on Azure. In order to resolve this issue the Windows Azure provides another storage serviec – Blob, for us. Different to the table service, the blob serivce is to be used to store text and binary data rather than the structured data. It provides two types of blobs: Block Blobs and Page Blobs. Block Blobs are optimized for streaming. They are comprised of blocks, each of which is identified by a block ID and each block can be a maximum of 4 MB in size. Page Blobs are are optimized for random read/write operations and provide the ability to write to a range of bytes in a blob. They are a collection of pages. The maximum size for a page blob is 1 TB.   In the managed library the Azure SDK allows us to communicate with the blobs through these classes CloudBlobClient, CloudBlobContainer, CloudBlockBlob and the CloudPageBlob. Similar with the table service managed library, the CloudBlobClient allows us to reach the blob service by passing our storage account information and also responsible for creating the blob container is not exist. Then from the CloudBlobContainer we can save or load the block blobs and page blobs into the CloudBlockBlob and the CloudPageBlob classes.   Let’s improve our exmaple in the previous posts – add a service method allows the user to upload the logo image. In the server side I created a method name UploadLogo with 2 parameters: email and image. Then I created the storage account from the config file. I also add the validation to ensure that the email passed in is valid. 1: var storageAccount = CloudStorageAccount.FromConfigurationSetting("DataConnectionString"); 2: var accountContext = new DynamicDataContext<Account>(storageAccount); 3:  4: // validation 5: var accountNumber = accountContext.Load() 6: .Where(a => a.Email == email) 7: .ToList() 8: .Count; 9: if (accountNumber <= 0) 10: { 11: throw new ApplicationException(string.Format("Cannot find the account with the email {0}.", email)); 12: } Then there are three steps for saving the image into the blob service. First alike the table service I created the container with a unique name and create it if it’s not exist. 1: // create the blob container for account logos if not exist 2: CloudBlobClient blobStorage = storageAccount.CreateCloudBlobClient(); 3: CloudBlobContainer container = blobStorage.GetContainerReference("account-logo"); 4: container.CreateIfNotExist(); Then, since in this example I will just send the blob access URL back to the client so I need to open the read permission on that container. 1: // configure blob container for public access 2: BlobContainerPermissions permissions = container.GetPermissions(); 3: permissions.PublicAccess = BlobContainerPublicAccessType.Container; 4: container.SetPermissions(permissions); And at the end I combine the blob resource name from the input file name and Guid, and then save it to the block blob by using the UploadByteArray method. Finally I returned the URL of this blob back to the client side. 1: // save the blob into the blob service 2: string uniqueBlobName = string.Format("{0}_{1}.jpg", email, Guid.NewGuid().ToString()); 3: CloudBlockBlob blob = container.GetBlockBlobReference(uniqueBlobName); 4: blob.UploadByteArray(image); 5:  6: return blob.Uri.ToString(); Let’s update a bit on the client side application and see the result. Here I just use my simple console application to let the user input the email and the file name of the image. If it’s OK it will show the URL of the blob on the server side so that we can see it through the web browser. Then we can see the logo I’ve just uploaded through the URL here. You may notice that the blob URL was based on the container name and the blob unique name. In the document of the Azure SDK there’s a page for the rule of naming them, but I think the simple rule would be – they must be valid as an URL address. So that you cannot name the container with dot or slash as it will break the ADO.Data Service routing rule. For exmaple if you named the blob container as Account.Logo then it will throw an exception says 400 Bad Request.   Summary In this short entity I covered the simple usage of the blob service to save the images onto Azure. Since the Azure platform does not support the file system we have to migrate our code for reading/writing files to the blob service before deploy it to Azure. In order to reducing this effort Microsoft provided a new approch named Drive, which allows us read and write the NTFS files just likes what we did before. It’s built up on the blob serivce but more properly for files accessing. I will discuss more about it in the next post.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • HDFC Bank's Journey to Oracle Private Database Cloud

    - by Nilesh Agrawal
    One of the key takeaways from a recent post by Sushil Kumar is the importance of business initiative that drives the transformational journey from legacy IT to enterprise private cloud. The journey that leads to a agile, self-service and efficient infrastructure with reduced complexity and enables IT to deliver services more closely aligned with business requirements. Nilanjay Bhattacharjee, AVP, IT of HDFC Bank presented a real-world case study based on one such initiative in his Oracle OpenWorld session titled "HDFC BANK Journey into Oracle Database Cloud with EM 12c DBaaS". The case study highlighted in this session is from HDFC Bank’s Lending Business Segment, which comprises roughly 50% of Bank’s top line. Bank’s Lending Business is always under pressure to launch “New Schemes” to compete and stay ahead in this segment and IT has to keep up with this challenging business requirement. Lending related applications are highly dynamic and go through constant changes and every single and minor change in each related application is required to be thoroughly UAT tested certified before they are certified for production rollout. This leads to a constant pressure in IT for rapid provisioning of UAT databases on an ongoing basis to enable faster time to market. Nilanjay joined Sushil Kumar, VP, Product Strategy, Oracle, during the Enterprise Manager general session at Oracle OpenWorld 2012. Let's watch what Nilanjay had to say about their recent Database cloud deployment. “Agility” in launching new business schemes became the key business driver for private database cloud adoption in the Bank. Nilanjay spent an hour discussing it during his session. Let's look at why Database-as-a-Service(DBaaS) model was need of the hour in this case  - Average 3 days to provision UAT Database for Loan Management Application Silo’ed UAT environment with Average 30% utilization Compliance requirement consume UAT testing resources DBA activities leads to $$ paid to SI for provisioning databases manually Overhead in managing configuration drift between production and test environments Rollout impact/delay on new business initiatives The private database cloud implementation progressed through 4 fundamental phases - Standardization, Consolidation, Automation, Optimization of UAT infrastructure. Project scoping was carried out and end users and stakeholders were engaged early on right from planning phase and including all phases of implementation. Standardization and Consolidation phase involved multiple iterations of planning to first standardize on infrastructure, db versions, patch levels, configuration, IT processes etc and with database level consolidation project onto Exadata platform. It was also decided to have existing AIX UAT DB landscape covered and EM 12c DBaaS solution being platform agnostic supported this model well. Automation and Optimization phase provided the necessary Agility, Self-Service and efficiency and this was made possible via EM 12c DBaaS. EM 12c DBaaS Self-Service/SSA Portal was setup with required zones, quotas, service templates, charge plan defined. There were 2 zones implemented - Exadata zone  primarily for UAT and benchmark testing for databases running on Exadata platform and second zone was for AIX setup to cover other databases those running on AIX. Metering and Chargeback/Showback capabilities provided business and IT the framework for cloud optimization and also visibility into cloud usage. More details on UAT cloud implementation, related building blocks and EM 12c DBaaS solution are covered in Nilanjay's OpenWorld session here. Some of the key Benefits achieved from UAT cloud initiative are - New business initiatives can be easily launched due to rapid provisioning of UAT Databases [ ~3 hours ] Drastically cut down $$ on SI for DBA Activities due to Self-Service Effective usage of infrastructure leading to  better ROI Empowering  consumers to provision database using Self-Service Control on project schedule with DB end date aligned to project plan submitted during provisioning Databases provisioned through Self-Service are monitored in EM and auto configured for Alerts and KPI Regulatory requirement of database does not impact existing project in queue This table below shows typical list of activities and tasks involved when a end user requests for a UAT database. EM 12c DBaaS solution helped reduce UAT database provisioning time from roughly 3 days down to 3 hours and this timing also includes provisioning time for database with production scale data (ranging from 250 G to 2 TB of data) - And it's not just about time to provision,  this initiative has enabled an agile, efficient and transparent UAT environment where end users are empowered with real control of cloud resources and IT's role is shifted as enabler of strategic services instead of being administrator of all user requests. The strong collaboration between IT and business community right from planning to implementation to go-live has played the key role in achieving this common goal of enterprise private cloud. Finally, real cloud is here and this cloud is accompanied with rain (business benefits) as well ! For more information, please go to Oracle Enterprise Manager  web page or  follow us at :  Twitter | Facebook | YouTube | Linkedin | Newsletter

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  • How to Buy an SD Card: Speed Classes, Sizes, and Capacities Explained

    - by Chris Hoffman
    Memory cards are used in digital cameras, music players, smartphones, tablets, and even laptops. But not all SD cards are created equal — there are different speed classes, physical sizes, and capacities to consider. Different devices require different types of SD cards. Here are the differences you’ll need to keep in mind when picking out the right SD card for your device. Speed Class In a nutshell, not all SD cards offer the same speeds. This matters for some tasks more than it matters for others. For example, if you’re a professional photographer taking photos in rapid succession on a DSLR camera saving them in high-resolution RAW format, you’ll want a fast SD card so your camera can save them as fast as possible. A fast SD card is also important if you want to record high-resolution video and save it directly to the SD card. If you’re just taking a few photos on a typical consumer camera or you’re just using an SD card to store some media files on your smartphone, the speed isn’t as important. Manufacturers use “speed classes” to measure an SD card’s speed. The SD Association that defines the SD card standard doesn’t actually define the exact speeds associated with these classes, but they do provide guidelines. There are four different speed classes — 10, 8, 4, and 2. 10 is the fastest, while 2 is the slowest. Class 2 is suitable for standard definition video recording, while classes 4 and 6 are suitable for high-definition video recording. Class 10 is suitable for “full HD video recording” and “HD still consecutive recording.” There are also two Ultra High Speed (UHS) speed classes, but they’re more expensive and are designed for professional use. UHS cards are designed for devices that support UHS. Here are the associated logos, in order from slowest to fastest:       You’ll probably be okay with a class 4 or 6 card for typical use in a digital camera, smartphone, or tablet. Class 10 cards are ideal if you’re shooting high-resolution videos or RAW photos. Class 2 cards are a bit on the slow side these days, so you may want to avoid them for all but the cheapest digital cameras. Even a cheap smartphone can record HD video, after all. An SD card’s speed class is identified on the SD card itself. You’ll also see the speed class on the online store listing or on the card’s packaging when purchasing it. For example, in the below photo, the middle SD card is speed class 4, while the two other cards are speed class 6. If you see no speed class symbol, you have a class 0 SD card. These cards were designed and produced before the speed class rating system was introduced. They may be slower than even a class 2 card. Physical Size Different devices use different sizes of SD cards. You’ll find standard-size CD cards, miniSD cards, and microSD cards. Standard SD cards are the largest, although they’re still very small. They measure 32x24x2.1 mm and weigh just two grams. Most consumer digital cameras for sale today still use standard SD cards. They have the standard “cut corner”  design. miniSD cards are smaller than standard SD cards, measuring 21.5x20x1.4 mm and weighing about 0.8 grams. This is the least common size today. miniSD cards were designed to be especially small for mobile phones, but we now have a smaller size. microSD cards are the smallest size of SD card, measuring 15x11x1 mm and weighing just 0.25 grams. These cards are used in most cell phones and smartphones that support SD cards. They’re also used in many other devices, such as tablets. SD cards will only fit into marching slots. You can’t plug a microSD card into a standard SD card slot — it won’t fit. However, you can purchase an adapter that allows you to plug a smaller SD card into a larger SD card’s form and fit it into the appropriate slot. Capacity Like USB flash drives, hard drives, solid-state drives, and other storage media, different SD cards can have different amounts of storage. But the differences between SD card capacities don’t stop there. Standard SDSC (SD) cards are 1 MB to 2 GB in size, or perhaps 4 GB in size — although 4 GB is non-standard. The SDHC standard was created later, and allows cards 2 GB to 32 GB in size. SDXC is a more recent standard that allows cards 32 GB to 2 TB in size. You’ll need a device that supports SDHC or SDXC cards to use them. At this point, the vast majority of devices should support SDHC. In fact, the SD cards you have are probably SDHC cards. SDXC is newer and less common. When buying an SD card, you’ll need to buy the right speed class, size, and capacity for your needs. Be sure to check what your device supports and consider what speed and capacity you’ll actually need. Image Credit: Ryosuke SEKIDO on Flickr, Clive Darra on Flickr, Steven Depolo on Flickr

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  • Why is my external USB hard drive sometimes completely inaccessible?

    - by Eliah Kagan
    I have an external USB hard drive, consisting of an 1 TB SATA drive in a Rosewill RX35-AT-SU SLV Aluminum 3.5" Silver USB 2.0 External Enclosure, plugged into my SONY VAIO VGN-NS310F laptop. It is plugged directly into the computer (not through a hub). The drive inside the enclosure is a 7200 rpm Western Digital, but I don't remember the exact model. I can remove the drive from the enclosure (again), if people think it's necessary to know that detail. The drive is formatted ext4. I mount it dynamically with udisks on my Lubuntu 11.10 system, usually automatically via PCManFM. (I have had Lubuntu 12.04 on this machine, and experienced all this same behavior with that too.) Every once in a while--once or twice a day--it becomes inaccessible, and difficult to unmount. Attempting to unmount it with sudo umount ... gives an error message saying the drive is in use and suggesting fuser and lsof to find out what is using it. Killing processes found to be using the drive with fuser and lsof is sometimes sufficient to let me unmount it, but usually isn't. Once the drive is unmounted or the machine is rebooted, the drive will not mount. Plugging in the drive and turning it on registers nothing on the computer. dmesg is unchanged. The drive's access light usually blinks vigorously, as though the drive is being accessed constantly. Then eventually, after I keep the drive off for a while (half an hour), I am able to mount it again. While the drive doesn't work on this machine for a while, it will work immediately on another machine running the same version of Ubuntu. Sometimes bringing it back over from the other machine seems to "fix" it. Sometimes it doesn't. The drive doesn't always stop being accessible while mounted, before becoming unmountable. Sometimes it works fine, I turn off the computer, I turn the computer back on, and I cannot mount the drive. Currently this is the only drive with which I have this problem, but I've had problems that I think are the same as this, with different drives, on different Ubuntu machines. This laptop has another external USB drive plugged into it regularly, which doesn't have this problem. Unplugging that drive before plugging in the "problem" drive doesn't fix the problem. I've opened the drive up and made sure the connections were tight in the past, and that didn't seem to help (any more than waiting the same amount of time that it took to open and close the drive, before attempting to remount it). Does anyone have any ideas about what could be causing this, what troubleshooting steps I should perform, and/or how I could fix this problem altogether? Update: I tried replacing the USB data cable (from the enclosure to the laptop), as Merlin suggested. I should've tried that long ago, since it fits the symptoms perfectly (the drive works on another machine, which would make sense because the cable would be bent at a different angle, possibly completing a circuit of frayed wires). Unfortunately, though, this did not help--I have the same problem with the new cable. I'll try to provide additional detailed information about the drive inside the enclosure, next time I'm able to get the drive working. (At the moment I don't have another machine available to attach it.) Major Update (28 June 2012) The drive seems to have deteriorated considerably. I think this is so, because I've attached it to another machine and gotten lots of errors about invalid characters, when copying files from it. I am less interested in recovering data from the drive than I am in figuring out what is wrong with it. I specifically want to figure out if the problem is the drive or the enclosure. Now, when I plug the drive into the original machine where I was having the problems, it still doesn't appear (including with sudo fdisk -l), but it is recognized by the kernel and messages are added to dmesg. Most of the message consist of errors like this, repeated many times: [ 7.707593] sd 5:0:0:0: [sdc] Unhandled sense code [ 7.707599] sd 5:0:0:0: [sdc] Result: hostbyte=invalid driverbyte=DRIVER_SENSE [ 7.707606] sd 5:0:0:0: [sdc] Sense Key : Medium Error [current] [ 7.707614] sd 5:0:0:0: [sdc] Add. Sense: Unrecovered read error [ 7.707621] sd 5:0:0:0: [sdc] CDB: Read(10): 28 00 00 00 00 00 00 00 08 00 [ 7.707636] end_request: critical target error, dev sdc, sector 0 [ 7.707641] Buffer I/O error on device sdc, logical block 0 Here are all the lines from dmesg starting with when the drive is recognized. Please note that: I'm back to running Lubuntu 12.04 on this machine (and perhaps that's a factor in better error messages). Now that the drive has been plugged into another machine and back into this one, and also now that this machine is back to running 12.04, the drive's access light doesn't blink as I had described. Looking at the drive, it would appear as though it is working normally, with low or no access. This behavior (the errors) occurs when rebooting the machine with the drive plugged in, and also when manually plugging in the drive. A few of the messages are about /dev/sdb. That drive is working fine. The bad drive is /dev/sdc. I just didn't want to edit anything out from the middle.

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  • SPARC T4-4 Delivers World Record First Result on PeopleSoft Combined Benchmark

    - by Brian
    Oracle's SPARC T4-4 servers running Oracle's PeopleSoft HCM 9.1 combined online and batch benchmark achieved World Record 18,000 concurrent users while executing a PeopleSoft Payroll batch job of 500,000 employees in 43.32 minutes and maintaining online users response time at < 2 seconds. This world record is the first to run online and batch workloads concurrently. This result was obtained with a SPARC T4-4 server running Oracle Database 11g Release 2, a SPARC T4-4 server running PeopleSoft HCM 9.1 application server and a SPARC T4-2 server running Oracle WebLogic Server in the web tier. The SPARC T4-4 server running the application tier used Oracle Solaris Zones which provide a flexible, scalable and manageable virtualization environment. The average CPU utilization on the SPARC T4-2 server in the web tier was 17%, on the SPARC T4-4 server in the application tier it was 59%, and on the SPARC T4-4 server in the database tier was 35% (online and batch) leaving significant headroom for additional processing across the three tiers. The SPARC T4-4 server used for the database tier hosted Oracle Database 11g Release 2 using Oracle Automatic Storage Management (ASM) for database files management with I/O performance equivalent to raw devices. This is the first three tier mixed workload (online and batch) PeopleSoft benchmark also processing PeopleSoft payroll batch workload. Performance Landscape PeopleSoft HR Self-Service and Payroll Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-2 (db) 18,000 0.944 0.503 43.32 64 Configuration Summary Application Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 512 GB memory 5 x 300 GB SAS internal disks 1 x 100 GB and 2 x 300 GB internal SSDs 2 x 10 Gbe HBA Oracle Solaris 11 11/11 PeopleTools 8.52 PeopleSoft HCM 9.1 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Java Platform, Standard Edition Development Kit 6 Update 32 Database Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 256 GB memory 3 x 300 GB SAS internal disks Oracle Solaris 11 11/11 Oracle Database 11g Release 2 Web Tier Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 2 x 300 GB SAS internal disks 1 x 100 GB internal SSD Oracle Solaris 11 11/11 PeopleTools 8.52 Oracle WebLogic Server 10.3.4 Java Platform, Standard Edition Development Kit 6 Update 32 Storage Configuration: 1 x Sun Server X2-4 as a COMSTAR head for data 4 x Intel Xeon X7550, 2.0 GHz 128 GB memory 1 x Sun Storage F5100 Flash Array (80 flash modules) 1 x Sun Storage F5100 Flash Array (40 flash modules) 1 x Sun Fire X4275 as a COMSTAR head for redo logs 12 x 2 TB SAS disks with Niwot Raid controller Benchmark Description This benchmark combines PeopleSoft HCM 9.1 HR Self Service online and PeopleSoft Payroll batch workloads to run on a unified database deployed on Oracle Database 11g Release 2. The PeopleSoft HRSS benchmark kit is a Oracle standard benchmark kit run by all platform vendors to measure the performance. It's an OLTP benchmark where DB SQLs are moderately complex. The results are certified by Oracle and a white paper is published. PeopleSoft HR SS defines a business transaction as a series of HTML pages that guide a user through a particular scenario. Users are defined as corporate Employees, Managers and HR administrators. The benchmark consist of 14 scenarios which emulate users performing typical HCM transactions such as viewing paycheck, promoting and hiring employees, updating employee profile and other typical HCM application transactions. All these transactions are well-defined in the PeopleSoft HR Self-Service 9.1 benchmark kit. This benchmark metric is the weighted average response search/save time for all the transactions. The PeopleSoft 9.1 Payroll (North America) benchmark demonstrates system performance for a range of processing volumes in a specific configuration. This workload represents large batch runs typical of a ERP environment during a mass update. The benchmark measures five application business process run times for a database representing large organization. They are Paysheet Creation, Payroll Calculation, Payroll Confirmation, Print Advice forms, and Create Direct Deposit File. The benchmark metric is the cumulative elapsed time taken to complete the Paysheet Creation, Payroll Calculation and Payroll Confirmation business application processes. The benchmark metrics are taken for each respective benchmark while running simultaneously on the same database back-end. Specifically, the payroll batch processes are started when the online workload reaches steady state (the maximum number of online users) and overlap with online transactions for the duration of the steady state. Key Points and Best Practices Two Oracle PeopleSoft Domain sets with 200 application servers each on a SPARC T4-4 server were hosted in 2 separate Oracle Solaris Zones to demonstrate consolidation of multiple application servers, ease of administration and performance tuning. Each Oracle Solaris Zone was bound to a separate processor set, each containing 15 cores (total 120 threads). The default set (1 core from first and third processor socket, total 16 threads) was used for network and disk interrupt handling. This was done to improve performance by reducing memory access latency by using the physical memory closest to the processors and offload I/O interrupt handling to default set threads, freeing up cpu resources for Application Servers threads and balancing application workload across 240 threads. See Also Oracle PeopleSoft Benchmark White Papers oracle.com SPARC T4-2 Server oracle.com OTN SPARC T4-4 Server oracle.com OTN PeopleSoft Enterprise Human Capital Management oracle.com OTN PeopleSoft Enterprise Human Capital Management (Payroll) oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Oracle's PeopleSoft HR and Payroll combined benchmark, www.oracle.com/us/solutions/benchmark/apps-benchmark/peoplesoft-167486.html, results 09/30/2012.

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  • Need help with testdisk output

    - by dan
    I had (note the past tense) an ubuntu 12.04 system with separate partitions for the base and /home directories. It started acting wonky, so I decided to do a reinstall with 12.10, intending just to do a reinstall to the base partition. After several seconds, I realize that the installer was repartitioning the drive and reinstalling, so I pulled the power cord. I'm now trying to recover as much as I can with testdisk, but it seems that testdisk is finding 100 unique partitions when I run it - they mostly tend to be HFS+ or solaris /home (which I think is just an ext4; I've never had solaris on the machine). I've pasted an abbreviated version of the testdisk output below (first ~100 lines, and then ~100 lines from the middle of the output). Is there a way to combine or recreate the partitions and then data recovery, or some other way maximize what I can recover (ideally as much of the file system as possible)? I really only care about what was in the /home directory - I'd rather not use photorec since I don't have another 2 TB HD lying around to recover to. Thanks, Dan Mon Dec 10 06:03:00 2012 Command line: TestDisk TestDisk 6.13, Data Recovery Utility, November 2011 Christophe GRENIER <[email protected]> http://www.cgsecurity.org OS: Linux, kernel 3.2.34-std312-amd64 (#2 SMP Sat Nov 17 08:06:32 UTC 2012) x86_64 Compiler: GCC 4.4 Compilation date: 2012-11-27T22:44:52 ext2fs lib: 1.42.6, ntfs lib: libntfs-3g, reiserfs lib: 0.3.1-rc8, ewf lib: none /dev/sda: LBA, HPA, LBA48, DCO support /dev/sda: size 3907029168 sectors /dev/sda: user_max 3907029168 sectors /dev/sda: native_max 3907029168 sectors Warning: can't get size for Disk /dev/mapper/control - 0 B - CHS 1 1 1, sector size=512 /dev/sr0 is not an ATA disk Hard disk list Disk /dev/sda - 2000 GB / 1863 GiB - CHS 243201 255 63, sector size=512 - WDC WD20EARS-00J2GB0, S/N:WD-WCAYY0075071, FW:80.00A80 Disk /dev/sdb - 1013 MB / 967 MiB - CHS 1014 32 61, sector size=512 - Generic Flash Disk, FW:8.07 Disk /dev/sr0 - 367 MB / 350 MiB - CHS 179470 1 1 (RO), sector size=2048 - PLDS DVD+/-RW DH-16AAS, FW:JD12 Partition table type (auto): Intel Disk /dev/sda - 2000 GB / 1863 GiB - WDC WD20EARS-00J2GB0 Partition table type: EFI GPT Analyse Disk /dev/sda - 2000 GB / 1863 GiB - CHS 243201 255 63 Current partition structure: Bad GPT partition, invalid signature. search_part() Disk /dev/sda - 2000 GB / 1863 GiB - CHS 243201 255 63 recover_EXT2: s_block_group_nr=0/14880, s_mnt_count=5/4294967295, s_blocks_per_group=32768, s_inodes_per_group=8192 recover_EXT2: s_blocksize=4096 recover_EXT2: s_blocks_count 487593984 recover_EXT2: part_size 3900751872 MS Data 2048 3900753919 3900751872 EXT4 Large file Sparse superblock, 1997 GB / 1860 GiB Linux Swap 3900755968 3907028975 6273008 SWAP2 version 1, 3211 MB / 3062 MiB Results P MS Data 2048 3900753919 3900751872 EXT4 Large file Sparse superblock, 1997 GB / 1860 GiB P Linux Swap 3900755968 3907028975 6273008 SWAP2 version 1, 3211 MB / 3062 MiB interface_write() 1 P MS Data 2048 3900753919 3900751872 2 P Linux Swap 3900755968 3907028975 6273008 search_part() Disk /dev/sda - 2000 GB / 1863 GiB - CHS 243201 255 63 recover_EXT2: s_block_group_nr=0/14880, s_mnt_count=5/4294967295, s_blocks_per_group=32768, s_inodes_per_group=8192 recover_EXT2: s_blocksize=4096 recover_EXT2: s_blocks_count 487593984 recover_EXT2: part_size 3900751872 MS Data 2048 3900753919 3900751872 EXT4 Large file Sparse superblock, 1997 GB / 1860 GiB block_group_nr 1 recover_EXT2: "e2fsck -b 32768 -B 4096 device" may be needed recover_EXT2: s_block_group_nr=1/14880, s_mnt_count=0/4294967295, s_blocks_per_group=32768, s_inodes_per_group=8192 recover_EXT2: s_blocksize=4096 recover_EXT2: s_blocks_count 487593984 recover_EXT2: part_size 3900751872 MS Data 2046 3900753917 3900751872 EXT4 Large file Sparse superblock Backup superblock, 1997 GB / 1860 GiB block_group_nr 1 recover_EXT2: "e2fsck -b 32768 -B 4096 device" may be needed recover_EXT2: s_block_group_nr=1/14880, s_mnt_count=0/4294967295, s_blocks_per_group=32768, s_inodes_per_group=8192 recover_EXT2: s_blocksize=4096 recover_EXT2: s_blocks_count 487593984 recover_EXT2: part_size 3900751872 MS Data 2048 3900753919 3900751872 EXT4 Large file Sparse superblock Backup superblock, 1997 GB / 1860 GiB block_group_nr 1 recover_EXT2: "e2fsck -b 32768 -B 4096 device" may be needed recover_EXT2: s_block_group_nr=1/14584, s_mnt_count=0/27, s_blocks_per_group=32768, s_inodes_per_group=8192 recover_EXT2: s_blocksize=4096 recover_EXT2: s_blocks_count 477915164 recover_EXT2: part_size 3823321312 MS Data 4094 3823325405 3823321312 EXT4 Large file Sparse superblock Backup superblock, 1957 GB / 1823 GiB block_group_nr 1 ....snip...... MS Data 2046 3900753917 3900751872 EXT4 Large file Sparse superblock Backup superblock, 1997 GB / 1860 GiB MS Data 2048 3900753919 3900751872 EXT4 Large file Sparse superblock, 1997 GB / 1860 GiB MS Data 4094 3823325405 3823321312 EXT4 Large file Sparse superblock Backup superblock, 1957 GB / 1823 GiB MS Data 4096 3823325407 3823321312 EXT4 Large file Sparse superblock Backup superblock, 1957 GB / 1823 GiB MS Data 7028840 7033383 4544 FAT12, 2326 KB / 2272 KiB Mac HFS 67856948 67862179 5232 HFS+ found using backup sector!, 2678 KB / 2616 KiB Mac HFS 67862176 67867407 5232 HFS+, 2678 KB / 2616 KiB Mac HFS 67862244 67867475 5232 HFS+ found using backup sector!, 2678 KB / 2616 KiB Mac HFS 67867404 67872635 5232 HFS+, 2678 KB / 2616 KiB Mac HFS 67867472 67872703 5232 HFS+, 2678 KB / 2616 KiB Mac HFS 67872700 67877931 5232 HFS+, 2678 KB / 2616 KiB Mac HFS 67937834 67948067 10234 [EasyInstall_OSX] HFS found using backup sector!, 5239 KB / 5117 KiB Mac HFS 67938012 67948155 10144 HFS+ found using backup sector!, 5193 KB / 5072 KiB Mac HFS 67948064 67958297 10234 [EasyInstall_OSX] HFS, 5239 KB / 5117 KiB Mac HFS 67948070 67958303 10234 [EasyInstall_OSX] HFS found using backup sector!, 5239 KB / 5117 KiB Mac HFS 67948152 67958295 10144 HFS+, 5193 KB / 5072 KiB Mac HFS 67958292 67968435 10144 HFS+, 5193 KB / 5072 KiB Mac HFS 67958300 67968533 10234 [EasyInstall_OSX] HFS, 5239 KB / 5117 KiB Mac HFS 67992596 67997827 5232 HFS+ found using backup sector!, 2678 KB / 2616 KiB Mac HFS 67997824 68003055 5232 HFS+, 2678 KB / 2616 KiB Mac HFS 67997892 68003123 5232 HFS+ found using backup sector!, 2678 KB / 2616 KiB Mac HFS 68003052 68008283 5232 HFS+, 2678 KB / 2616 KiB Mac HFS 68003120 68008351 5232 HFS+, 2678 KB / 2616 KiB Mac HFS 68008348 68013579 5232 HFS+, 2678 KB / 2616 KiB Solaris /home 84429840 123499141 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84429952 123499253 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84493136 123562437 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84493248 123562549 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84566088 123635389 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84566200 123635501 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84571232 123640533 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84571344 123640645 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84659952 123729253 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84660064 123729365 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84690504 123759805 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84690616 123759917 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84700424 123769725 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84700536 123769837 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84797720 123867021 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84797832 123867133 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84812544 123881845 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84812656 123881957 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84824552 123893853 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84824664 123893965 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84847528 123916829 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84847640 123916941 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84886840 123956141 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84886952 123956253 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84945488 124014789 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84945600 124014901 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84957992 124027293 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84958104 124027405 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84962240 124031541 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84962352 124031653 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84977168 124046469 39069302 UFS1, 20 GB / 18 GiB Solaris /home 84977280 124046581 39069302 UFS1, 20 GB / 18 GiB MS Data 174395467 178483851 4088385 ..... snip (it keeps going on for quite a while)

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  • External USB 3 drive not recognized

    - by ilan123
    Ubuntu 12.10 64 bit seems not to recognize my external hard disk. It is a Vantec NST-310S3 external disk enclosure with a WD 3TB drive. The disk has two NTFS partitions. My PC is a dual boot system. Under Windows 7 the hard disk works fine but I can't make it work with Ubuntu. When the drive is connected to the PC then the command sudo fdisk -l seems to hang forever. Below are the output of lsusb and cat /proc/partitions without the external drive and then with it connected. I added also the last lines of the dmesg command at the end. First without the drive: ilan@linux:~$ lsusb Bus 001 Device 002: ID 8087:0024 Intel Corp. Integrated Rate Matching Hub Bus 002 Device 002: ID 8087:0024 Intel Corp. Integrated Rate Matching Hub Bus 001 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 002 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 003 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 004 Device 001: ID 1d6b:0003 Linux Foundation 3.0 root hub Bus 001 Device 003: ID 13ba:0017 Unknown PS/2 Keyboard+Mouse Adapter Bus 001 Device 004: ID 046d:c50e Logitech, Inc. Cordless Mouse Receiver Bus 001 Device 005: ID 0ac8:3420 Z-Star Microelectronics Corp. Venus USB2.0 Camera ilan@linux:~$ cat /proc/partitions major minor #blocks name 8 0 1953514584 sda 8 1 102400 sda1 8 2 629043200 sda2 8 3 367001600 sda3 8 4 1 sda4 8 5 471859200 sda5 8 6 157286400 sda6 8 7 324115456 sda7 8 8 4101120 sda8 11 0 1048575 sr0 Second with the USB 3 drive: ilan@linux:~$ lsusb Bus 001 Device 002: ID 8087:0024 Intel Corp. Integrated Rate Matching Hub Bus 002 Device 002: ID 8087:0024 Intel Corp. Integrated Rate Matching Hub Bus 004 Device 002: ID 174c:55aa ASMedia Technology Inc. Bus 001 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 002 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 003 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 004 Device 001: ID 1d6b:0003 Linux Foundation 3.0 root hub Bus 001 Device 003: ID 13ba:0017 Unknown PS/2 Keyboard+Mouse Adapter Bus 001 Device 004: ID 046d:c50e Logitech, Inc. Cordless Mouse Receiver Bus 001 Device 005: ID 0ac8:3420 Z-Star Microelectronics Corp. Venus USB2.0 Camera ilan@linux:~$ cat /proc/partitions major minor #blocks name 8 0 1953514584 sda 8 1 102400 sda1 8 2 629043200 sda2 8 3 367001600 sda3 8 4 1 sda4 8 5 471859200 sda5 8 6 157286400 sda6 8 7 324115456 sda7 8 8 4101120 sda8 11 0 1048575 sr0 8 16 2930266584 sdb ilan@linux:~$ lsusb -v -s 004:002 Bus 004 Device 002: ID 174c:55aa ASMedia Technology Inc. Couldn't open device, some information will be missing Device Descriptor: bLength 18 bDescriptorType 1 bcdUSB 3.00 bDeviceClass 0 (Defined at Interface level) bDeviceSubClass 0 bDeviceProtocol 0 bMaxPacketSize0 9 idVendor 0x174c ASMedia Technology Inc. idProduct 0x55aa bcdDevice 1.00 iManufacturer 2 iProduct 3 iSerial 1 bNumConfigurations 1 Configuration Descriptor: bLength 9 bDescriptorType 2 wTotalLength 44 bNumInterfaces 1 bConfigurationValue 1 iConfiguration 0 bmAttributes 0xc0 Self Powered MaxPower 0mA Interface Descriptor: bLength 9 bDescriptorType 4 bInterfaceNumber 0 bAlternateSetting 0 bNumEndpoints 2 bInterfaceClass 8 Mass Storage bInterfaceSubClass 6 SCSI bInterfaceProtocol 80 Bulk-Only iInterface 0 Endpoint Descriptor: bLength 7 bDescriptorType 5 bEndpointAddress 0x81 EP 1 IN bmAttributes 2 Transfer Type Bulk Synch Type None Usage Type Data wMaxPacketSize 0x0400 1x 1024 bytes bInterval 0 bMaxBurst 15 Endpoint Descriptor: bLength 7 bDescriptorType 5 bEndpointAddress 0x02 EP 2 OUT bmAttributes 2 Transfer Type Bulk Synch Type None Usage Type Data wMaxPacketSize 0x0400 1x 1024 bytes bInterval 0 bMaxBurst 15 ilan@linux:~$ sudo fdisk -l [sudo] password for ilan: Disk /dev/sda: 2000.4 GB, 2000398934016 bytes 255 heads, 63 sectors/track, 243201 cylinders, total 3907029168 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0xf1b4f1ee Device Boot Start End Blocks Id System /dev/sda1 * 2048 206847 102400 7 HPFS/NTFS/exFAT /dev/sda2 206848 1258293247 629043200 7 HPFS/NTFS/exFAT /dev/sda3 1258293248 1992296447 367001600 7 HPFS/NTFS/exFAT /dev/sda4 1992298494 3907028991 957365249 f W95 Ext'd (LBA) /dev/sda5 1992298496 2936016895 471859200 7 HPFS/NTFS/exFAT /dev/sda6 2936018944 3250591743 157286400 7 HPFS/NTFS/exFAT /dev/sda7 3250593792 3898824703 324115456 83 Linux /dev/sda8 3898826752 3907028991 4101120 82 Linux swap / Solaris dmesg output after connecting the external drive: [ 23.740567] e1000e: eth0 NIC Link is Up 1000 Mbps Full Duplex, Flow Control: Rx/Tx [ 23.740786] IPv6: ADDRCONF(NETDEV_CHANGE): eth0: link becomes ready [ 49.144673] usb 4-1: >new SuperSpeed USB device number 2 using xhci_hcd [ 49.163039] usb 4-1: >Parent hub missing LPM exit latency info. Power management will be impacted. [ 49.166789] usb 4-1: >New USB device found, idVendor=174c, idProduct=55aa [ 49.166793] usb 4-1: >New USB device strings: Mfr=2, Product=3, SerialNumber=1 [ 49.166796] usb 4-1: >Product: AS2105 [ 49.166799] usb 4-1: >Manufacturer: ASMedia [ 49.166801] usb 4-1: >SerialNumber: 0123456789ABCDEF [ 49.206372] usbcore: registered new interface driver uas [ 49.228891] Initializing USB Mass Storage driver... [ 49.229042] scsi6 : usb-storage 4-1:1.0 [ 49.229115] usbcore: registered new interface driver usb-storage [ 49.229116] USB Mass Storage support registered. [ 64.045528] scsi 6:0:0:0: >Direct-Access WDC WD30 EZRX-00MMMB0 80.0 PQ: 0 ANSI: 0 [ 64.046224] sd 6:0:0:0: >Attached scsi generic sg2 type 0 [ 64.046881] sd 6:0:0:0: >[sdb] Very big device. Trying to use READ CAPACITY(16). [ 64.047610] sd 6:0:0:0: >[sdb] 5860533168 512-byte logical blocks: (3.00 TB/2.72 TiB) [ 64.048368] sd 6:0:0:0: >[sdb] Write Protect is off [ 64.048373] sd 6:0:0:0: >[sdb] Mode Sense: 23 00 00 00 [ 64.048984] sd 6:0:0:0: >[sdb] No Caching mode page present [ 64.048987] sd 6:0:0:0: >[sdb] Assuming drive cache: write through [ 64.049297] sd 6:0:0:0: >[sdb] Very big device. Trying to use READ CAPACITY(16). [ 64.050942] sd 6:0:0:0: >[sdb] No Caching mode page present [ 64.050944] sd 6:0:0:0: >[sdb] Assuming drive cache: write through [ 94.245006] usb 4-1: >reset SuperSpeed USB device number 2 using xhci_hcd [ 94.262553] usb 4-1: >Parent hub missing LPM exit latency info. Power management will be impacted. [ 94.263805] xhci_hcd 0000:03:00.0: >xHCI xhci_drop_endpoint called with disabled ep ffff8800d37d1c00 [ 94.263808] xhci_hcd 0000:03:00.0: >xHCI xhci_drop_endpoint called with disabled ep ffff8800d37d1c40 [ 125.262722] usb 4-1: >reset SuperSpeed USB device number 2 using xhci_hcd [ 125.280304] usb 4-1: >Parent hub missing LPM exit latency info. Power management will be impacted. [ 125.281511] xhci_hcd 0000:03:00.0: >xHCI xhci_drop_endpoint called with disabled ep ffff8800d37d1c00 [ 125.281516] xhci_hcd 0000:03:00.0: >xHCI xhci_drop_endpoint called with disabled ep ffff8800d37d1c40

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  • Installing Ubuntu 12.04.1 x64 with Fake RAID 1 [SOLVED]

    - by Arkadius
    I had: Software: Dual boot with Windows XP Ubuntu 10.04 LTS x32 Hardware Fake RAID 1 (mirroring) with 2x1 TB: Partition 1 - Windows Partition 2 - SWAP Partition 3 - / (root) Partition 4 - Extended Partition 5 - /home Partition 6 - /data arek@domek:/var/log/installer$ sudo fdisk -l Disk /dev/sda: 1000.2 GB, 1000204886016 bytes 255 heads, 63 sectors/track, 121601 cylinders, total 1953525168 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0x000de1b9 Device Boot Start End Blocks Id System /dev/sda1 * 63 524297339 262148638+ 7 HPFS/NTFS/exFAT /dev/sda2 524297340 528506369 2104515 82 Linux swap / Solaris /dev/sda3 528506370 570468149 20980890 83 Linux /dev/sda4 570468150 1953118439 691325145 5 Extended /dev/sda5 570468213 675340469 52436128+ 83 Linux /dev/sda6 675340533 1953118439 638888953+ 83 Linux Disk /dev/sdb: 1000.2 GB, 1000204886016 bytes 255 heads, 63 sectors/track, 121601 cylinders, total 1953525168 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0x000de1b9 Device Boot Start End Blocks Id System /dev/sdb1 * 63 524297339 262148638+ 7 HPFS/NTFS/exFAT /dev/sdb2 524297340 528506369 2104515 82 Linux swap / Solaris /dev/sdb3 528506370 570468149 20980890 83 Linux /dev/sdb4 570468150 1953118439 691325145 5 Extended /dev/sdb5 570468213 675340469 52436128+ 83 Linux /dev/sdb6 675340533 1953118439 638888953+ 83 Linux arek@domek:/var/log/installer$ ls -l /dev/mapper/ total 0 crw------- 1 root root 10, 236 Oct 7 20:17 control lrwxrwxrwx 1 root root 7 Oct 7 20:17 pdc_jhjbcaha -> ../dm-0 lrwxrwxrwx 1 root root 7 Oct 7 20:17 pdc_jhjbcaha1 -> ../dm-1 lrwxrwxrwx 1 root root 7 Oct 7 20:17 pdc_jhjbcaha2 -> ../dm-2 lrwxrwxrwx 1 root root 7 Oct 7 20:17 pdc_jhjbcaha3 -> ../dm-3 lrwxrwxrwx 1 root root 7 Oct 7 20:17 pdc_jhjbcaha4 -> ../dm-4 lrwxrwxrwx 1 root root 7 Oct 7 20:17 pdc_jhjbcaha5 -> ../dm-5 lrwxrwxrwx 1 root root 7 Oct 7 20:17 pdc_jhjbcaha6 -> ../dm-6 I wanted to upgrade from 10.04 x32 to 12.04 x64 using FRESH installation. So, run installation of Ubuntu 12.04.1 x64 LTS using alternate CD. During the installation I selected manual partitioning and to: - Use and Format / (root) - Use and Format SWAP - Use and Keep data on /home - Use and Keep data on /data After I clicked "Continue" I get error creating and formatting SWAP partition. I go to terminal with Alt + F2 (?) and hit enter. I discovered that there was visible RAID as only disk with NO partitions. Something like this: arek@domek:/var/log/installer$ ls -l /dev/mapper/ lrwxrwxrwx 1 root root 7 Oct 7 20:17 /dev/mapper/pdc_jhjbcaha -> ../dm-0 arek@domek:/var/log/installer$ ls -l /dev/dm* brw-rw---- 1 root disk 252, 0 Oct 7 20:17 /dev/dm-0 So I switched to log console Alt+F3 (?) and saw errors like below: Oct 7 14:02:45 check-missing-firmware: /dev/.udev/firmware-missing does not exist, skipping Oct 7 14:02:45 check-missing-firmware: /run/udev/firmware-missing does not exist, skipping Oct 7 14:02:45 check-missing-firmware: no missing firmware in /dev/.udev/firmware-missing /run/udev/firmware-missing Oct 7 14:02:45 anna-install: Installing dmraid-udeb Oct 7 14:02:45 anna[12599]: DEBUG: retrieving dmraid-udeb 1.0.0.rc16-4.1ubuntu8 Oct 7 14:02:49 anna[12599]: DEBUG: retrieving libdmraid1.0.0.rc16-udeb 1.0.0.rc16-4.1ubuntu8 Oct 7 14:02:49 anna[12599]: DEBUG: retrieving kpartx-udeb 0.4.9-3ubuntu5 Oct 7 14:02:49 disk-detect: Serial ATA RAID disk(s) detected. Oct 7 14:02:55 disk-detect: Enabling dmraid support. Oct 7 14:02:55 disk-detect: RAID set "pdc_jhjbcaha" was activated Oct 7 14:02:55 HERE --> dmraid-activate: ERROR: Cannot retrieve RAID set information for pdc_jhjbcaha Oct 7 14:02:56 check-missing-firmware: /dev/.udev/firmware-missing does not exist, skipping Oct 7 14:02:56 check-missing-firmware: /run/udev/firmware-missing does not exist, skipping Oct 7 14:02:56 check-missing-firmware: no missing firmware in /dev/.udev/firmware-missing /run/udev/firmware-missing Oct 7 14:02:57 main-menu[428]: DEBUG: resolver (libnewt0.52): package doesn't exist (ignored) Oct 7 14:02:57 main-menu[428]: DEBUG: resolver (ext2-modules): package doesn't exist (ignored) Oct 7 14:02:57 main-menu[428]: INFO: Menu item 'partman-base' selected Oct 7 14:02:57 kernel: [ 316.512999] NTFS driver 2.1.30 [Flags: R/O MODULE]. Oct 7 14:02:57 kernel: [ 316.523221] Btrfs loaded Oct 7 14:02:57 kernel: [ 316.534781] JFS: nTxBlock = 8192, nTxLock = 65536 Oct 7 14:02:57 kernel: [ 316.554749] SGI XFS with ACLs, security attributes, realtime, large block/inode numbers, no debug enabled Oct 7 14:02:57 kernel: [ 316.555336] SGI XFS Quota Management subsystem Oct 7 14:02:58 md-devices: mdadm: No arrays found in config file or automatically Oct 7 14:02:58 partman: No matching physical volumes found Oct 7 14:02:58 partman: No volume groups found Oct 7 14:02:58 partman: Reading all physical volumes. This may take a while... Oct 7 14:02:58 partman-lvm: No volume groups found Oct 7 14:02:58 partman: Error running 'tune2fs -l /dev/mapper/pdc_jhjbcaha' Oct 7 14:02:58 partman: Error running 'tune2fs -l /dev/mapper/pdc_jhjbcaha' Oct 7 14:02:58 partman: Error running 'tune2fs -l /dev/mapper/pdc_jhjbcaha' Oct 7 14:06:11 HERE --> partman: mkswap: can't open '/dev/mapper/pdc_jhjbcaha2': No such file or directory Oct 7 14:07:28 init: starting pid 401, tty '/dev/tty2': '-/bin/sh' Oct 7 14:15:00 net/hw-detect.hotplug: Detected hotpluggable network interface eth0 Oct 7 14:15:00 net/hw-detect.hotplug: Detected hotpluggable network interface lo As You can see there are 2 errors Oct 7 14:02:55 dmraid-activate: ERROR: Cannot retrieve RAID set information for pdc_jhjbcaha and Oct 7 14:06:11 partman: mkswap: can't open '/dev/mapper/pdc_jhjbcaha2': No such file or directory I looked in the internet and try to run command "dmraid -ay" and get something like that: dmraid -ay /dev/mapper/pdc_jhjbcaha -> Already activated /dev/mapper/pdc_jhjbcaha1 -> Successfully activated /dev/mapper/pdc_jhjbcaha2 -> Successfully activated /dev/mapper/pdc_jhjbcaha3 -> Successfully activated /dev/mapper/pdc_jhjbcaha4 -> Successfully activated /dev/mapper/pdc_jhjbcaha5 -> Successfully activated /dev/mapper/pdc_jhjbcaha6 -> Successfully activated Then I returned to installer with Alt+F1 (?) and click "Return" to return to partitioning menu. I did NOT change anything just selected again "Continue" and everything goes smoothly. I hope this will help someone. arkadius

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  • SPARC T4-4 Delivers World Record Performance on Oracle OLAP Perf Version 2 Benchmark

    - by Brian
    Oracle's SPARC T4-4 server delivered world record performance with subsecond response time on the Oracle OLAP Perf Version 2 benchmark using Oracle Database 11g Release 2 running on Oracle Solaris 11. The SPARC T4-4 server achieved throughput of 430,000 cube-queries/hour with an average response time of 0.85 seconds and the median response time of 0.43 seconds. This was achieved by using only 60% of the available CPU resources leaving plenty of headroom for future growth. The SPARC T4-4 server operated on an Oracle OLAP cube with a 4 billion row fact table of sales data containing 4 dimensions. This represents as many as 90 quintillion aggregate rows (90 followed by 18 zeros). Performance Landscape Oracle OLAP Perf Version 2 Benchmark 4 Billion Fact Table Rows System Queries/hour Users* Response Time (sec) Average Median SPARC T4-4 430,000 7,300 0.85 0.43 * Users - the supported number of users with a given think time of 60 seconds Configuration Summary and Results Hardware Configuration: SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 1 TB memory Data Storage 1 x Sun Fire X4275 (using COMSTAR) 2 x Sun Storage F5100 Flash Array (each with 80 FMODs) Redo Storage 1 x Sun Fire X4275 (using COMSTAR with 8 HDD) Software Configuration: Oracle Solaris 11 11/11 Oracle Database 11g Release 2 (11.2.0.3) with Oracle OLAP option Benchmark Description The Oracle OLAP Perf Version 2 benchmark is a workload designed to demonstrate and stress the Oracle OLAP product's core features of fast query, fast update, and rich calculations on a multi-dimensional model to support enhanced Data Warehousing. The bulk of the benchmark entails running a number of concurrent users, each issuing typical multidimensional queries against an Oracle OLAP cube consisting of a number of years of sales data with fully pre-computed aggregations. The cube has four dimensions: time, product, customer, and channel. Each query user issues approximately 150 different queries. One query chain may ask for total sales in a particular region (e.g South America) for a particular time period (e.g. Q4 of 2010) followed by additional queries which drill down into sales for individual countries (e.g. Chile, Peru, etc.) with further queries drilling down into individual stores, etc. Another query chain may ask for yearly comparisons of total sales for some product category (e.g. major household appliances) and then issue further queries drilling down into particular products (e.g. refrigerators, stoves. etc.), particular regions, particular customers, etc. Results from version 2 of the benchmark are not comparable with version 1. The primary difference is the type of queries along with the query mix. Key Points and Best Practices Since typical BI users are often likely to issue similar queries, with different constants in the where clauses, setting the init.ora prameter "cursor_sharing" to "force" will provide for additional query throughput and a larger number of potential users. Except for this setting, together with making full use of available memory, out of the box performance for the OLAP Perf workload should provide results similar to what is reported here. For a given number of query users with zero think time, the main measured metrics are the average query response time, the median query response time, and the query throughput. A derived metric is the maximum number of users the system can support achieving the measured response time assuming some non-zero think time. The calculation of the maximum number of users follows from the well-known response-time law N = (rt + tt) * tp where rt is the average response time, tt is the think time and tp is the measured throughput. Setting tt to 60 seconds, rt to 0.85 seconds and tp to 119.44 queries/sec (430,000 queries/hour), the above formula shows that the T4-4 server will support 7,300 concurrent users with a think time of 60 seconds and an average response time of 0.85 seconds. For more information see chapter 3 from the book "Quantitative System Performance" cited below. -- See Also Quantitative System Performance Computer System Analysis Using Queueing Network Models Edward D. Lazowska, John Zahorjan, G. Scott Graham, Kenneth C. Sevcik external local Oracle Database 11g – Oracle OLAP oracle.com OTN SPARC T4-4 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 11/2/2012.

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  • How do I mount my External HDD with filesystem type errors?

    - by Snuggie
    I am a relatively new Ubuntu user and I am having some difficulty mounting my external 2TB HDD. When I first installed Linux my external HDD was working just fine, however, it has stopped working and I have a lot of important files on there that I need. Before my HDD would automatically mount and no worries. Now, however, it doesn't automatically mount and when I try to manually mount it I keep running into filesystem type errors that I can't seem to get past. Below are images that depict my step by step process of how I am trying to mount my HDD along with the errors I am receiving. If anybody has any idea what I am doing wrong or how to correct the issue I would greatly appreciate it. Step 1) Ensure the computer recognizes my external HDD. pj@PJ:~$ dmesg ... [ 5790.367910] scsi 7:0:0:0: Direct-Access WD My Passport 0748 1022 PQ: 0 ANSI: 6 [ 5790.368278] scsi 7:0:0:1: Enclosure WD SES Device 1022 PQ: 0 ANSI: 6 [ 5790.370122] sd 7:0:0:0: Attached scsi generic sg2 type 0 [ 5790.370310] ses 7:0:0:1: Attached Enclosure device [ 5790.370462] ses 7:0:0:1: Attached scsi generic sg3 type 13 [ 5792.971601] sd 7:0:0:0: [sdb] 3906963456 512-byte logical blocks: (2.00 TB/1.81 TiB) [ 5792.972148] sd 7:0:0:0: [sdb] Write Protect is off [ 5792.972162] sd 7:0:0:0: [sdb] Mode Sense: 47 00 10 08 [ 5792.972591] sd 7:0:0:0: [sdb] No Caching mode page found [ 5792.972605] sd 7:0:0:0: [sdb] Assuming drive cache: write through [ 5792.975235] sd 7:0:0:0: [sdb] No Caching mode page found [ 5792.975249] sd 7:0:0:0: [sdb] Assuming drive cache: write through [ 5792.987504] sdb: sdb1 [ 5792.988900] sd 7:0:0:0: [sdb] No Caching mode page found [ 5792.988911] sd 7:0:0:0: [sdb] Assuming drive cache: write through [ 5792.988920] sd 7:0:0:0: [sdb] Attached SCSI disk Step 2) Check if it mounted properly (it does not) pj@PJ:~$ df -ah Filesystem Size Used Avail Use% Mounted on /dev/sda1 682G 3.9G 644G 1% / proc 0 0 0 - /proc sysfs 0 0 0 - /sys none 0 0 0 - /sys/fs/fuse/connections none 0 0 0 - /sys/kernel/debug none 0 0 0 - /sys/kernel/security udev 2.9G 4.0K 2.9G 1% /dev devpts 0 0 0 - /dev/pts tmpfs 1.2G 928K 1.2G 1% /run none 5.0M 0 5.0M 0% /run/lock none 2.9G 156K 2.9G 1% /run/shm gvfs-fuse-daemon 0 0 0 - /home/pj/.gvfs Step 3) Try mounting manually using NTFS and VFAT (both as SDB and SDB1) pj@PJ:~$ sudo mount /dev/sdb /media/Passport/ NTFS signature is missing. Failed to mount '/dev/sdb': Invalid argument The device '/dev/sdb' doesn't seem to have a valid NTFS. Maybe the wrong device is used? Or the whole disk instead of a partition (e.g. /dev/sda, not /dev/sda1)? Or the other way around? pj@PJ:~$ sudo mount /dev/sdb1 /media/Passport/ NTFS signature is missing. Failed to mount '/dev/sdb1': Invalid argument The device '/dev/sdb1' doesn't seem to have a valid NTFS. Maybe the wrong device is used? Or the whole disk instead of a partition (e.g. /dev/sda, not /dev/sda1)? Or the other way around? pj@PJ:~$ sudo mount -t ntfs /dev/sdb /media/Passport/ NTFS signature is missing. Failed to mount '/dev/sdb': Invalid argument The device '/dev/sdb' doesn't seem to have a valid NTFS. Maybe the wrong device is used? Or the whole disk instead of a partition (e.g. /dev/sda, not /dev/sda1)? Or the other way around? pj@PJ:~$ sudo mount -t vfat /dev/sdb /media/Passport/ mount: wrong fs type, bad option, bad superblock on /dev/sdb, missing codepage or helper program, or other error In some cases useful info is found in syslog - try dmesg | tail or so pj@PJ:~$ sudo mount -t ntfs /dev/sdb1 /media/Passport/ NTFS signature is missing. Failed to mount '/dev/sdb1': Invalid argument The device '/dev/sdb1' doesn't seem to have a valid NTFS. Maybe the wrong device is used? Or the whole disk instead of a partition (e.g. /dev/sda, not /dev/sda1)? Or the other way around? pj@PJ:~$ sudo mount -t vfat /dev/sdb1 /media/Passport/ mount: wrong fs type, bad option, bad superblock on /dev/sdb1, missing codepage or helper program, or other error In some cases useful info is found in syslog - try dmesg | tail or so

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  • Oracle NoSQL Database Exceeds 1 Million Mixed YCSB Ops/Sec

    - by Charles Lamb
    We ran a set of YCSB performance tests on Oracle NoSQL Database using SSD cards and Intel Xeon E5-2690 CPUs with the goal of achieving 1M mixed ops/sec on a 95% read / 5% update workload. We used the standard YCSB parameters: 13 byte keys and 1KB data size (1,102 bytes after serialization). The maximum database size was 2 billion records, or approximately 2 TB of data. We sized the shards to ensure that this was not an "in-memory" test (i.e. the data portion of the B-Trees did not fit into memory). All updates were durable and used the "simple majority" replica ack policy, effectively 'committing to the network'. All read operations used the Consistency.NONE_REQUIRED parameter allowing reads to be performed on any replica. In the past we have achieved 100K ops/sec using SSD cards on a single shard cluster (replication factor 3) so for this test we used 10 shards on 15 Storage Nodes with each SN carrying 2 Rep Nodes and each RN assigned to its own SSD card. After correcting a scaling problem in YCSB, we blew past the 1M ops/sec mark with 8 shards and proceeded to hit 1.2M ops/sec with 10 shards.  Hardware Configuration We used 15 servers, each configured with two 335 GB SSD cards. We did not have homogeneous CPUs across all 15 servers available to us so 12 of the 15 were Xeon E5-2690, 2.9 GHz, 2 sockets, 32 threads, 193 GB RAM, and the other 3 were Xeon E5-2680, 2.7 GHz, 2 sockets, 32 threads, 193 GB RAM.  There might have been some upside in having all 15 machines configured with the faster CPU, but since CPU was not the limiting factor we don't believe the improvement would be significant. The client machines were Xeon X5670, 2.93 GHz, 2 sockets, 24 threads, 96 GB RAM. Although the clients had 96 GB of RAM, neither the NoSQL Database or YCSB clients require anywhere near that amount of memory and the test could have just easily been run with much less. Networking was all 10GigE. YCSB Scaling Problem We made three modifications to the YCSB benchmark. The first was to allow the test to accommodate more than 2 billion records (effectively int's vs long's). To keep the key size constant, we changed the code to use base 32 for the user ids. The second change involved to the way we run the YCSB client in order to make the test itself horizontally scalable.The basic problem has to do with the way the YCSB test creates its Zipfian distribution of keys which is intended to model "real" loads by generating clusters of key collisions. Unfortunately, the percentage of collisions on the most contentious keys remains the same even as the number of keys in the database increases. As we scale up the load, the number of collisions on those keys increases as well, eventually exceeding the capacity of the single server used for a given key.This is not a workload that is realistic or amenable to horizontal scaling. YCSB does provide alternate key distribution algorithms so this is not a shortcoming of YCSB in general. We decided that a better model would be for the key collisions to be limited to a given YCSB client process. That way, as additional YCSB client processes (i.e. additional load) are added, they each maintain the same number of collisions they encounter themselves, but do not increase the number of collisions on a single key in the entire store. We added client processes proportionally to the number of records in the database (and therefore the number of shards). This change to the use of YCSB better models a use case where new groups of users are likely to access either just their own entries, or entries within their own subgroups, rather than all users showing the same interest in a single global collection of keys. If an application finds every user having the same likelihood of wanting to modify a single global key, that application has no real hope of getting horizontal scaling. Finally, we used read/modify/write (also known as "Compare And Set") style updates during the mixed phase. This uses versioned operations to make sure that no updates are lost. This mode of operation provides better application behavior than the way we have typically run YCSB in the past, and is only practical at scale because we eliminated the shared key collision hotspots.It is also a more realistic testing scenario. To reiterate, all updates used a simple majority replica ack policy making them durable. Scalability Results In the table below, the "KVS Size" column is the number of records with the number of shards and the replication factor. Hence, the first row indicates 400m total records in the NoSQL Database (KV Store), 2 shards, and a replication factor of 3. The "Clients" column indicates the number of YCSB client processes. "Threads" is the number of threads per process with the total number of threads. Hence, 90 threads per YCSB process for a total of 360 threads. The client processes were distributed across 10 client machines. Shards KVS Size Clients Mixed (records) Threads OverallThroughput(ops/sec) Read Latencyav/95%/99%(ms) Write Latencyav/95%/99%(ms) 2 400m(2x3) 4 90(360) 302,152 0.76/1/3 3.08/8/35 4 800m(4x3) 8 90(720) 558,569 0.79/1/4 3.82/16/45 8 1600m(8x3) 16 90(1440) 1,028,868 0.85/2/5 4.29/21/51 10 2000m(10x3) 20 90(1800) 1,244,550 0.88/2/6 4.47/23/53

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  • #OOW 2012 : IaaS, Private Cloud, Multitenant Database, and X3H2M2

    - by Eric Bezille
    The title of this post is a summary of the 4 announcements made by Larry Ellison today, during the opening session of Oracle Open World 2012... To know what's behind X3H2M2, you will have to wait a little, as I will go in order, beginning with the IaaS - Infrastructure as a Service - announcement. Oracle IaaS goes Public... and Private... Starting in 2004 with Fusion development, Oracle Cloud was launch last year to provide not only SaaS Application, based on standard development, but also the underlying PaaS, required to build the specifics, and required interconnections between applications, in and outside of the Cloud. Still, to cover the end-to-end Cloud  Services spectrum, we had to provide an Infrastructure as a Service, leveraging our Servers, Storage, OS, and Virtualization Technologies, all "Engineered Together". This Cloud Infrastructure, was already available for our customers to build rapidly their own Private Cloud either on SPARC/Solaris or x86/Linux... The second announcement made today bring that proposition a big step further : for cautious customers (like Banks, or sensible industries) who would like to benefits from the Cloud value of "as a Service", but don't want their Data out in the Cloud... We propose to them to operate the same systems, Exadata, Exalogic & SuperCluster, that are providing our Public Cloud Infrastructure, behind their firewall, in a Private Cloud model. Oracle 12c Multitenant Database This is also a major announcement made today, on what's coming with Oracle Database 12c : the ability to consolidate multiple databases with no extra additional  cost especially in terms of memory needed on the server node, which is often THE consolidation limiting factor. The principle could be compare to Solaris Zones, where, you will have a Database Container, who is "owning" the memory and Database background processes, and "Pluggable" Database in this Database Container. This particular feature is a strong compelling event to evaluate rapidly Oracle Database 12c once it will be available, as this is major step forward into true Database consolidation with Multitenancy on a shared (optimized) infrastructure. X3H2M2, enabling the new Exadata X3 in-Memory Database Here we are :  X3H2M2 stands for X3 (the new version of Exadata announced also today) Heuristic Hierarchical Mass Memory, providing the capability to keep most if not all the Data in the memory cache hierarchy. Of course, this is the major software enhancement of the new X3 Exadata machine, but as this is a software, our current customers would be able to benefit from it on their existing systems by upgrading to the new release. But that' not the only thing that we did with X3, at the same time we have upgraded everything : the CPUs, adding more cores per server node (16 vs. 12, with the arrival of Intel E5 / Sandy Bridge), the memory with 512GB memory as well per node,  and the new Flash Fire card, bringing now up to 22 TB of Flash cache. All of this 4TB of RAM + 22TB of Flash being use cleverly not only for read but also for write by the X3H2M2 algorithm... making a very big difference compare to traditional storage flash extension. But what does those extra performances brings to you on an already very efficient system: double your performances compare to the fastest storage array on the market today (including flash) and divide you storage price x10 at the same time... Something to consider closely this days... Especially that we also announced the availability of a new Exadata X3-2 8th rack : a good starting point. As you have seen a major opening for this year again with true innovation. But that was not the only thing that we saw today, as before Larry's talk, Fujitsu did introduce more in deep the up coming new SPARC processor, that they are co-developing with us. And as such Andrew Mendelsohn - Senior Vice President Database Server Technologies came on stage to explain that the next step after I/O optimization for Database with Exadata, was to accelerate the Database at execution level by bringing functions in the SPARC processor silicium. All in all, to process more and more Data... The big theme of the day... and of the Oracle User Groups Conferences that were also happening today and where I had the opportunity to attend some interesting sessions on practical use cases of Big Data one in Finances and Fraud profiling and the other one on practical deployment of Oracle Exalytics for Data Analytics. In conclusion, one picture to try to size Oracle Open World ... and you can understand why, with such a rich content... and this only the first day !

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  • Tomcat 403 error after LDAP authentication.

    - by user352636
    I'm currently trying to use an LDAP server to authenticate users who are trying to access our Tomcat setup. I believe I have managed to get the LDAP authentication working in the form of a JNDI realm call from Tomcat, but immediately after the user enters their password Tomcat starts throwing 403 (permission denied) errors for everything except from the root page (ttp://localhost:1337/). I have no idea why this is happening. I am following the example at http://blog.mc-thias.org/?title=tomcat_ldap_authentication&more=1&c=1&tb=1&pb=1 . server.xml (the interesting/changed bits) <Realm className="org.apache.catalina.realm.JNDIRealm" debug="99" connectionURL="ldap://localhost:389" userPattern="uid={0},ou=People,o=test,dc=company,dc=uk" userSubTree="true" roleBase="ou=Roles,o=test,dc=company,dc=uk" roleName="cn" roleSearch="memberUid={1}" /> <Valve className="org.apache.catalina.authenticator.SingleSignOn" /> web.xml (the interesting/changed bits) <security-constraint> <display-name>Security Constraint</display-name> <web-resource-collection> <web-resource-name>Protected Area</web-resource-name> <!-- Define the context-relative URL(s) to be protected --> <url-pattern>/*</url-pattern> <!-- If you list http methods, only those methods are protected --> </web-resource-collection> <auth-constraint> <!-- Anyone with one of the listed roles may access this area --> <role-name>admin</role-name> <role-name>regular</role-name> </auth-constraint> </security-constraint> <!-- Default login configuration uses form-based authentication --> <login-config> <auth-method>BASIC</auth-method> </login-config> <!-- Security roles referenced by this web application --> <security-role> <role-name>admin</role-name> <role-name>regular</role-name> </security-role> I cannot access my LDAP setup at the moment, but I believe it is alright as the login is accepted by the BASIC auth method, it's just tomcat that is rejecting it. The roles should be as defined in web.xml - admin and regular. If there is any other information you require me to provide, please just ask! My thanks in advance to anyone who can help, and my apologies for any major mistakes I have made - yesterday was pretty much the first time I'd ever heard of LDAP =D. EDIT: Fixed the second xml segment. Apologies for the formating-fail.

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  • Oracle Schema Design: Seperate Schema with I/O Overhead?

    - by Guru
    We are designing database schema for a new system based on Oracle 11gR1. We have identified a main schema which would have close to 100 tables, these will be accessed from the front end Java application. We have a requirement to audit the values which got changed in close to 50 tables, this has to be done every row. Which means, it is possible that, for a single row in MYSYS.T1 there might be 50 (or more) rows in MYSYS_AUDIT.T1_AUD table. We might be having old values of every column entry and new values available from T1. DBA gave an observation, advising against this method, because he said, separate schema meant an extra I/O for every operation. Basically AUDIT schema would be used only to do some analyse and enter values (thus SELECT and INSERT). Is it true that, "a separate schema means an extra I/O" ? I could not find justification. It appears logical to me, as the AUDIT data should not be tampered with, so a separate schema. Also, we designed a separate schema for archiving some tables from MYSYS. From MYSYS_ARC the table might be backed up into tapes or deleted after sufficient time. Few stats: Few tables (close to 20, 30) in MYSYS schema could grow to around 50M rows. We have asked for a total disk space of 4 TB. MYSYS_AUDIT schema might be having 10 times that of MYSYS but we wont keep them more than 3 months. Questions Given all these, can you suggest me any improvements? Separate schema affects disc I/O? (one extra I/O for every schema ?) Any general suggestions? Figure: +-------------------+ +-------------------+ | MYSYS | | MYSYS_AUDIT | | | | | | 1. T1 | | 1. T1_AUD | | 2. T2 | | 2. T2_AUD | | 3. T3 |--------->| 3. T3_AUD | | 4. T4 |(SELECT, | 4. T4_AUD | | . | INSERT) | . | | . | | . | | . | | . | | 100. T100 | | 50. T50_AUD | +-------------------+ +-------------------+ | | | | |(INSERT) | | | * +-------------------+ | MYSYS_ARC | | | | 1. T1_ARC | | 2. T2_ARC | | 3. T3_ARC | | 4. T4_ARC | | . | | . | | . | | 100. T100_ARC | +-------------------+ Apart from this, we have two more schemas with only read only rights, but mainly they are for adhoc purpose and we dont mind the performance on them.

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  • Is there a way to handle the dynamic change of a dropdown for a single row in a grid-based datawindo

    - by TomatoSandwich
    Is there a way to handle the dynamic change of a dropdown for a single row in a grid-based datawindow? Example: NAME LIKABILITY PURCHASED IN COLOUR (Text) (DropDown*) (Text) (Text) Bananas [Good] Hands Yellow [Bad] [Bananas are good] Apples [Good] Bags Red [Bad] Given the above is a grid-based datawindow, where the fields 'NAME','PURCHASED IN' and 'COLOUR' are text fields, where as the 'LIKABILITY' field is a dropdown*. I say dropdown* because the same visual representation can be created by using a DropDownList (hardcoded within the datawindow element at design time), or a DropDownDW (or DDDW, a select statement that can be based on other elements in the datawindow). However, there is no way I can get 'Bananas' having it's 3 dropdowns, while Apples has only 2. If I enter multiple rows of 'Bananas', then all rows have 3 dropdowns, but as soon as I add an Apples row, all dropdowns revert to 2 selections. To attempt to achieve this functionality, I have tried the following options: -- 1) dw_1.Object.likability.values("Good~tG/Bad~tB/Bananas are good~tDRWHO") on ue_itemchange when editing NAME. FAILS: edits all instances of LIKABILITY instead of the current row. -- 2) Duplicate Dropdowns, having one filtered, one unfiltered selection list per row, visible based on NAME selection. FAILS: can't set visibility/overlapping columns on grid-based datawindow. (Source) -- 3) Hard-code display value as Database value, or Vice Versa. Have 'GOOD','BAD','BANANASAREGOOD' as the display and database values, and change handling of options from G, B, DRWHO to these new values. FAILS: 3rd option appears for all rows, still selectable on Apple rows, which is wrong. -- 4) DDDW retrieve list of options for dropdown. Create a DDDW that uses the value of NAME to determine what selections it should have for the dropdown. FAILS: edits all instances of the dropdown, not just the current row. -- 5) DDDW retrieve counter of options available (if B then 3 else 2), then have duplicate dropdown columns that protect/unprotect based on DDDW counter. FAILS: Can't autoselect dddw value to populate column to cause protect on other two columns, ugly solution in any case. -- There is now a bounty on this question for anyone who can give me a solution that will enable me to edit a dropdown column for a single row on a grid-based datawindow in PB 10.5

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  • What are the types and inner workings of a query optimizer?

    - by Frank Developer
    As I understand it, most query optimizers are cost-based. Some can be influenced by hints like FIRST_ROWS(). Others are tailored for OLAP. Is it possible to know more detailed logic about how Informix IDS and SE's optimizers decide what's the best route for processing a query, other than SET EXPLAIN? Is there any documentation which illustrates the ranking of SELECT statements? I would imagine that "SELECT col FROM table WHERE ROWID = n" ranks 1st. What are the rest of them?.. If I'm not mistaking, Informix's ROWID is a SERIAL(INT) which allows for a max. of 2GB nrows, or maybe it uses INT9 for TB's nrows?.. However, I think Oracle uses HEX values for ROWID. Too bad ROWID can't be oftenly used, since a rows ROWID can change. So maybe ROWID is used by the optimizer as a counter? Perhaps, it could be used for implementing the query progress idea I mentioned in my "Begin viewing query results before query completes" question? For some reason, I feel it wouldn't be that difficult to report a query's progress while being processed, perhaps at the expense of some slight overhead, but it would be nice to know ahead of time: A "Google-like" estimate of how many rows meet a query's criteria, display it's progress every 100, 200, 500 or 1,000 rows, give users the ability to cancel it at anytime and start displaying the qualifying rows as they are being put into the current list, while it continues searching?.. This is just one example, perhaps we could think other neat/useful features, the ingridients are more or less there. Perhaps we could fine-tune each query with more granularity than currently available? OLTP queries tend to be mostly static and pre-defined. The "what-if's" are more OLAP, so let's try to add more control and intelligence to it? So, therefore, being able to more precisely control, not "hint-influence" a query is what's needed and therefore it would be necessary to know how the optimizers logic is programmed. We can then have Dynamic SELECT and other statements for specific situations! Maybe even tell IDS to read blocks of indexes nodes at-a-time instead of one-by-one, etc. etc.

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  • Cakephp file upload problem.

    - by vatismarty
    I am using Cakephp as my framework. I have a problem in uploading my files through a form. I am using an Uploader plugin from THIS website. My php ini file has this piece of code. upload_max_filesize = 10M post_max_size = 8M this is from uploader.php -- plugin file has var $maxFileSize = '5M'; //default max file size In my controller.php file, i use this code to set max file size as 1 MB at runtime. function beforeFilter() { parent::beforeFilter(); $this->Uploader->maxFileSize = '1M'; } In the uploader.php, we perform this ... if (empty($this->maxFileSize)) { $this->maxFileSize = ini_get('upload_max_filesize'); //landmark 1 } $byte = preg_replace('/[^0-9]/i', '', $this->maxFileSize); $last = $this->bytes($this->maxFileSize, 'byte'); if ($last == 'T' || $last == 'TB') { $multiplier = 1; $execTime = 20; } else if ($last == 'G' || $last == 'GB') { $multiplier = 3; $execTime = 10; } else if ($last == 'M' || $last == 'MB') { $multiplier = 5; $execTime = 5; } else { $multiplier = 10; $execTime = 3; } ini_set('memore_limit', (($byte * $multiplier) * $multiplier) . $last); ini_set('post_max_size', ($byte * $multiplier) . $last); //error suspected here ini_set('upload_tmp_dir', $this->tempDir); ini_set('upload_max_filesize', $this->maxFileSize); //landmark 2 EXPECTED RESULT: When i try uploading a file that is 2MB of size, it shouldn't take place because maxFileSize is 1MB at run time. So upload should fail. THE PROBLEM IS : But it is getting uploaded. Landmark 1 does not get executed. (in comments)... land mark 2 does not seem to work... upload_max_filesize does not get the value from maxFileSize. Please help me... thank you

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  • I have to do two seemingly mutually exclusive things on leaving an asp:textbox. Please help me get

    - by aape
    This project has gone from being a simple '99 Ford F-150 to the Homer. I've got controls with a gridview with textboxes for data entry. All the user controls on the pages are in AJAX updatepanels. User types in a database column or budget entity or some other financial thing they want to include in the report. The textboxes in the gridview have autopostback = true set. overly long background info When the user leaves the textbox, during the postback (triggered by onTextChanged) I do some validation back on the server on their entry - regexs, do they have rights to that column, is that column locked, etc. If it fails, I put a error message next to the textbox. If it passes, I wipe out any title or error that used to be next to the code. Focus is getting lost from the postback if they're tabbing out of the box, rather than going to the next textbox in the gridview. So to fix that I need, if their leaving the tb via the tab key, to also figure out what textbox or gridviewrow they're on, if they're not on the last row, and after the validation and labeling, put the focus on the textbox in the next row. I can't figure out how, in ontextchanged, to find what caused me to leave the textbox, so I'm thinking use javascript onkeyup to test the key pressed and then find the next box etc, but the ontextchanged fires first and then the js never does, and also, since the control is all AJAXed, the javascript can't find the textboxes because when you enter the page everything is collapsed (the requirements people loooove to collapse and expand things), and so when it's expanded, all the 'new' textboxes are up in the viewstate stuff in the page source, and not down where javascript can see them. The questions So I'm wondering if I can have an onblur in the javascript that can trigger a postback where I can do my validation and such, and either 1) include the keypressed or pick it out of sender in the event or 2) followup the onblur with onkeyup and somehow figure out what textbox is next on the grid and throw focus there. Or, is there another .NET based approach that could work for this? In terms of tearing the whole thing down and starting from scratch, I couldn't sell that to the bosses, I'm past the point of no return as far as that goes.

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