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  • Using Transaction Logging to Recover Post-Archived Essbase data

    - by Keith Rosenthal
    Data recovery is typically performed by restoring data from an archive.  Data added or removed since the last archive took place can also be recovered by enabling transaction logging in Essbase.  Transaction logging works by writing transactions to a log store.  The information in the log store can then be recovered by replaying the log store entries in sequence since the last archive took place.  The following information is recorded within a transaction log entry: Sequence ID Username Start Time End Time Request Type A request type can be one of the following categories: Calculations, including the default calculation as well as both server and client side calculations Data loads, including data imports as well as data loaded using a load rule Data clears as well as outline resets Locking and sending data from SmartView and the Spreadsheet Add-In.  Changes from Planning web forms are also tracked since a lock and send operation occurs during this process. You can use the Display Transactions command in the EAS console or the query database MAXL command to view the transaction log entries. Enabling Transaction Logging Transaction logging can be enabled at the Essbase server, application or database level by adding the TRANSACTIONLOGLOCATION essbase.cfg setting.  The following is the TRANSACTIONLOGLOCATION syntax: TRANSACTIONLOGLOCATION [appname [dbname]] LOGLOCATION NATIVE ENABLE | DISABLE Note that you can have multiple TRANSACTIONLOGLOCATION entries in the essbase.cfg file.  For example: TRANSACTIONLOGLOCATION Hyperion/trlog NATIVE ENABLE TRANSACTIONLOGLOCATION Sample Hyperion/trlog NATIVE DISABLE The first statement will enable transaction logging for all Essbase applications, and the second statement will disable transaction logging for the Sample application.  As a result, transaction logging will be enabled for all applications except the Sample application. A location on a physical disk other than the disk where ARBORPATH or the disk files reside is recommended to optimize overall Essbase performance. Configuring Transaction Log Replay Although transaction log entries are stored based on the LOGLOCATION parameter of the TRANSACTIONLOGLOCATION essbase.cfg setting, copies of data load and rules files are stored in the ARBORPATH/app/appname/dbname/Replay directory to optimize the performance of replaying logged transactions.  The default is to archive client data loads, but this configuration setting can be used to archive server data loads (including SQL server data loads) or both client and server data loads. To change the type of data to be archived, add the TRANSACTIONLOGDATALOADARCHIVE configuration setting to the essbase.cfg file.  Note that you can have multiple TRANSACTIONLOGDATALOADARCHIVE entries in the essbase.cfg file to adjust settings for individual applications and databases. Replaying the Transaction Log and Transaction Log Security Considerations To replay the transactions, use either the Replay Transactions command in the EAS console or the alter database MAXL command using the replay transactions grammar.  Transactions can be replayed either after a specified log time or using a range of transaction sequence IDs. The default when replaying transactions is to use the security settings of the user who originally performed the transaction.  However, if that user no longer exists or that user's username was changed, the replay operation will fail. Instead of using the default security setting, add the REPLAYSECURITYOPTION essbase.cfg setting to use the security settings of the administrator who performs the replay operation.  REPLAYSECURITYOPTION 2 will explicitly use the security settings of the administrator performing the replay operation.  REPLAYSECURITYOPTION 3 will use the administrator security settings if the original user’s security settings cannot be used. Removing Transaction Logs and Archived Replay Data Load and Rules Files Transaction logs and archived replay data load and rules files are not automatically removed and are only removed manually.  Since these files can consume a considerable amount of space, the files should be removed on a periodic basis. The transaction logs should be removed one database at a time instead of all databases simultaneously.  The data load and rules files associated with the replayed transactions should be removed in chronological order from earliest to latest.  In addition, do not remove any data load and rules files with a timestamp later than the timestamp of the most recent archive file. Partitioned Database Considerations For partitioned databases, partition commands such as synchronization commands cannot be replayed.  When recovering data, the partition changes must be replayed manually and logged transactions must be replayed in the correct chronological order. If the partitioned database includes any @XREF commands in the calc script, the logged transactions must be selectively replayed in the correct chronological order between the source and target databases. References For additional information, please see the Oracle EPM System Backup and Recovery Guide.  For EPM 11.1.2.2, the link is http://docs.oracle.com/cd/E17236_01/epm.1112/epm_backup_recovery_1112200.pdf

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  • How to determine the source of a request in a distributed service system?

    - by Kabumbus
    Map/Reduce is a great concept for sorting large quantities of data at once. What to do if you have small parts of data and you need to reduce it all the time? Simple example - choosing a service for request. Imagine we have 10 services. Each provides services host with sets of request headers and post/get arguments. Each service declares it has 30 unique keys - 10 per set. service A: name id ... Now imagine we have a distributed services host. We have 200 machines with 10 services on each. Each service has 30 unique keys in there sets. but now to find to which service to map the incoming request we make our services post unique values that map to that sets. We can have up to or more than 10 000 such values sets on each machine per each service. service A machine 1 name = Sam id = 13245 ... service A machine 1 name = Ben id = 33232 ... ... service A machine 100 name = Ron id = 777888 ... So we get 200 * 10 * 30 * 30 * 10 000 == 18 000 000 000 and we get 500 requests per second on our gateway each containing 45 items 15 of which are just noise. And our task is to find a service for request (at least a machine it is running on). On all machines all over cluster for same services we have same rules. We can first select to which service came our request via rules filter 10 * 30. and we will have 200 * 30 * 10 000 == 60 000 000. So... 60 mil is definitely a problem... I hope to get on idea of mapping 30 * 10 000 onto some artificial neural network alike Perceptron that outputs 1 if 30 words (some hashes from words) from the request are correct or if less than Perceptron should return 0. And I’ll send each such Perceptron for each service from each machine to gateway. So I would have a map Perceptron <-> machine for each service. Can any one tall me if my Perceptron idea is at least “sane”? Or normal people do it some other way? Or if there are better ANNs for such purposes?

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  • JTA or LOCAL transactions in JPA2+Hibernate 3.6.0?

    - by Pangea
    We are in the process of re-thinking our tech stack and below are our choices (We can't live without Spring and Hibernate due to the complexity etc of the app). We are also moving from J2EE 1.4 to JEE 5. Tech stack JEE 5 JPA 2.0 (I know JEE 5 only supports JPA 1.0 but we want to use Hibernate as the JPA provider) Hibernate 3.6.0 (We already have lots of hbm files with custom types etc. so we doesn't want to migrate them at this time to JPA. This means we want both jpa/hbm mappings work together and hence the Hibernate as the JPA provider instead of using the default that comes with App Server) Now the problems is that I want to stick with local transactions but other team members want to use JTA. I have been working with J2EE for last 9 years and I've heard time and again people suggesting to stick with local transactions if I doesn't need two phase commits. This is not only for performance reasons but debugging/troubleshooting a local transaction is lot easier than a distributed transaction. My suggestion is to use spring declarative transaction management + local transactions (HibernateTransactionManager) I want to make sure if I am being paranoid or I have a valid point. I'd like to hear what the rest of the JEE world thinks. Thank you.

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  • SQL SERVER – Concurrancy Problems and their Relationship with Isolation Level

    - by pinaldave
    Concurrency is simply put capability of the machine to support two or more transactions working with the same data at the same time. This usually comes up with data is being modified, as during the retrieval of the data this is not the issue. Most of the concurrency problems can be avoided by SQL Locks. There are four types of concurrency problems visible in the normal programming. 1)      Lost Update – This problem occurs when there are two transactions involved and both are unaware of each other. The transaction which occurs later overwrites the transactions created by the earlier update. 2)      Dirty Reads – This problem occurs when a transactions selects data that isn’t committed by another transaction leading to read the data which may not exists when transactions are over. Example: Transaction 1 changes the row. Transaction 2 changes the row. Transaction 1 rolls back the changes. Transaction 2 has selected the row which does not exist. 3)      Nonrepeatable Reads – This problem occurs when two SELECT statements of the same data results in different values because another transactions has updated the data between the two SELECT statements. Example: Transaction 1 selects a row, which is later on updated by Transaction 2. When Transaction A later on selects the row it gets different value. 4)      Phantom Reads – This problem occurs when UPDATE/DELETE is happening on one set of data and INSERT/UPDATE is happening on the same set of data leading inconsistent data in earlier transaction when both the transactions are over. Example: Transaction 1 is deleting 10 rows which are marked as deleting rows, during the same time Transaction 2 inserts row marked as deleted. When Transaction 1 is done deleting rows, there will be still rows marked to be deleted. When two or more transactions are updating the data, concurrency is the biggest issue. I commonly see people toying around with isolation level or locking hints (e.g. NOLOCK) etc, which can very well compromise your data integrity leading to much larger issue in future. Here is the quick mapping of the isolation level with concurrency problems: Isolation Dirty Reads Lost Update Nonrepeatable Reads Phantom Reads Read Uncommitted Yes Yes Yes Yes Read Committed No Yes Yes Yes Repeatable Read No No No Yes Snapshot No No No No Serializable No No No No I hope this 400 word small article gives some quick understanding on concurrency issues and their relation to isolation level. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Is make -j distcc possible to scale over 5 times?

    - by holmes
    Since distcc cannot keep states and just possible to send jobs and headers and let those servers to use only the data just sent and preprocess and compile, I think the lastest distcc has problem in scalability. In my local build environment which has appx. 10,000 c/c++ files to build, I could only make 2 times faster than not using distcc (but using make -j) when having 20 build servers. What do you think is the problem? If anyone has achieved scalability more than 10 - 20 times using make -j and distcc, please let me know. The following product claims that it is impossible to scale make -j and distcc faster than 5 times. http://www.electric-cloud.com/products/electricaccelerator.php I think this can be improved by: Letting the distccd server to maintain sessions Tied to those sessions, they will cache their own header directories Preprocess will be done demand base from the distccd server This will be done through a LD_PRELOADed library libdistcc.so which will replace stat/open syscalls and fetches the header files over network. ... Has anyone done this kind of thing?

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  • Memcached with Windows and .NET

    - by Funky81
    Is there anyone already implement memcached for production use in Windows environment? Because many blogs that I've read, it's not recommended to run memcached in Windows especially for production use, for example running memcached on windows. And one more thing, which memcached client that is good to use with c# and .net 3.5 ? I've found many alternate such as Memcached Providers @ Codeplex, Beitmemcached, and memcached provider @ Sourceforge

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  • Hadoop streaming job : stuck

    - by Algorist
    Hi, I am running a hadoop streaming job. It got stuck due to no reason. I am not sure how to cancel the task, so that hadoop schedules another task for the same job. I tried killing the job, but it still doesn't work. Anyone know, how to do this? Thank you Bala

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  • Best method of achieving bi-directional communication between Apple iPad "clients" and a Windows Ser

    - by user361910
    We are currently starting to build a client-server system which will see 10 or more Apple iPad client devices communicating to a central Windows server over a wireless LAN. We wanted to some existing plumbing (.NET remoting/WCF/web services/etc) that would allow us to implement a reliable, secure solution without having to start at a low level (e.g. sockets) and recreate the wheel. One of the major requirements that complicates this scenario is that unlike a traditional web service, the windows server needs to be able to arbitrarily notify the clients whenever certain events occur -- so it is not a simple request/response scenario like the web. Initially, we were going to use Windows clients, so our plan was to use the full-duplex mode of .NET WCF over HTTP|TCP. But now using the iPad, we don't have any of the WCF infrastructure. So my question is: what is the best way to allow an iPad and a Windows server to (securely) communicate over a LAN, with each device able to initiate communication to the other? Am I stuck writing low-level socket code? Thanks!

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  • Windows RPC vs XML-RPC

    - by Y.Z
    Is there any benchmark about encoding/decoding certain common typed data in Microsoft RPC NDR engine (DCE 1.1) in comparison with that in XML-RPC-C/C++ in the de-facto C/C++ implementation in XML-RPC? Actually I have to choose between Windows RPC and XML-RPC-C/C++ to implement my own common object infrastructure for High Performance Computing on Windows. Any recommandation about which with regard to their performance? Thank you. Best Regards, Yang

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  • Java Meta Search Engine API

    - by Loki
    I'm currently researching Java libraries to help in building a meta type search engine in the sense of being able to replace any given search engine in the back-end of the application or to simultaneously search using multiple search engines. I'm not interested in the GUI part here, just the generalization of search engine APIs and usage. I'd like to know about the common libraries used to achieve this task and if there are any common patterns used in this case. I imagined that this problem is common enough to be able to find plenty of stuff on Google, but it seems like search is a very proprietary domain and not much information is fed back to the community.

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  • Erlang: How to view output of io:format/2 calls in processes spawned on remote nodes.

    - by jkndrkn
    Hello, I am working on a decentralized Erlang application. I am currently working on a single PC and creating multiple nodes by initializing erl with the -sname flag. When I spawn a process using spawn/4 on its home node, I can see output generated by calls io:format/2 within that process in its home erl instance. When I spawn a process remotely by using spawn/4 in combination with register_name, output of io:format/2 is sometimes redirected back to the erl instance where the remote spawn/4 call was made, and sometimes remains completely invisible. Similarly, when I use rpc:call/4, output of io:format/2 calls is redirected back to the erl instance where the `rpc:call/4' call is made. How do you get a process to emit debugging output back to its parent erl instance?

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  • Which DHT algorithm to use (if I want to join two separate DHTs)?

    - by webdreamer
    I've been looking into some DHT systems, specially Pastry and Chord. I've read some concerns about Chord's reaction to churn, though I believe that won't be a problem for the task I have at hands. I'm implementing some sort of social network service that doesn't rely on any central servers for a course project. I need the DHT for the lookups. Now I don't know of all the servers in the network in the beginning. As I've stated, there's no main tracker server. It works this way: each client has three dedicated servers. The three servers have the profile of the client, and it's wall, it's personal info, replicated. I only get to know about other group of servers when the user adds a friend (inputing the client's address). So I would create two separate DHTs on the two groups of three servers and when they friend each other I would like to join the DHTs. I would like to this consistently. I haven't had a lot of time to get all that familiar with the protocols, so I would like to know which one is better if I want to join the two separate DHTs?

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  • How to Profile R Code that Includes SNOW Cluster

    - by James
    Hi, I have a nested loop that I'm using foreach, DoSNOW, and a SNOW socket cluster to solve for. How should I go about profiling the code to make sure I'm not doing something grossly inefficient. Also is there anyway to measure the data flows going between the master and nodes in a Snow cluster? Thanks, James

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  • Mercurial local branching and pushing to shared repository

    - by Steve Horn
    I created a branch on my local Mercurial repository. I want to push to the shared repository so my work can be backed up, but I don't want other project members to see the branch. What's the standard operating procedure in this case? I'd like to avoid having the repository get full of developer branches that I don't need to see.

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  • Best strategy for moving data between physical tiers in ASP.net

    - by Pete Lunenfeld
    Building a new ASP.net application, and planning to separate DB, 'service' tier and Web/UI tier into separate physical layers. What is the best/easiest strategy to move serialized objects between the service tier and the UI tier? I was considering serializing POCOs into JSON using simple ASP.net pages to serve the middle tier. Meaning that the UI/Web tier will request data from a (hidden to the outside user) web server that will return a JSON string. This kind of JSON 'emitter' seems easily testable. It also seems easily compressible for efficiently moving data over the WAN between tiers. I know that some folks use .asmx webservices for this kind of task, but this seems like there is excess overhead with SOAP, and the package is not as human readable (testable) as POCOs serialized as JSON. Others are using more complex technology like WCF which we have never used. Does anyone have advice for choosing a method for moving data/objects between the data (db) tier and the web (UI) tier over the WAN using .net technologies? Thanks!!!

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  • Can sphinx be used over cassandra?

    - by Mickey Shine
    I am planning to build a cassandra store system and also I need a full-text(Chinese) system too. Can sphinx be used on cassandra? (sphinx supports xml format but I am not going to use it, cause it is slow and much of time are spent on xml parsing). Or you can share your experiences if you have ever built a full-text searching system over cassandra. Thank you

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  • Why isn't Hadoop implemented using MPI?

    - by artif
    Correct me if I'm wrong, but my understanding is that Hadoop does not use MPI for communication between different nodes. What are the technical reasons for this? I could hazard a few guesses, but I do not know enough of how MPI is implemented "under the hood" to know whether or not I'm right. Come to think of it, I'm not entirely familiar with Hadoop's internals either. I understand the framework at a conceptual level (map/combine/shuffle/reduce and how that works at a high level) but I don't know the nitty gritty implementation details. I've always assumed Hadoop was transmitting serialized data structures (perhaps GPBs) over a TCP connection, eg during the shuffle phase. Let me know if that's not true.

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  • Is there an use case for non-blocking receive when I have threads?

    - by Gabriel Šcerbák
    I know non-blocking receive is not used as much in message passing, but still some intuition tells me, it is needed. Take for example GUI event driven applications, you need some way to wait for a message in a non-blocking way, so your program can execute some computations. One of the ways to solve this is to have a special thread with message queue. Is there some use case, where you would really need non-blocking receive even if you have threads?

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  • Is AMQP suitable as both an intra and inter-machine software bus?

    - by Bwooce
    I'm trying to get my head around AMQP. It looks great for inter-machine (cluster, LAN, WAN) communication between applications but I'm not sure if it is suitable (in architectural, and current implementation terms) for use as a software bus within one machine. Would it be worth pulling out a current high performance message passing framework to replace it with AMQP, or is this falling into the same trap as RPC by blurring the distinction between local and non-local communication? I'm also wary of the performance impacts of using a WAN technology for intra-machine communications, although this may be more of an implementation concern than architecture. War stories would be appreciated.

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  • How to design a high-level application protocol for metadata syncing between devices and server?

    - by Jaanus
    I am looking for guidance on how to best think about designing a high-level application protocol to sync metadata between end-user devices and a server. My goal: the user can interact with the application data on any device, or on the web. The purpose of this protocol is to communicate changes made on one endpoint to other endpoints through the server, and ensure all devices maintain a consistent picture of the application data. If user makes changes on one device or on the web, the protocol will push data to the central repository, from where other devices can pull it. Some other design thoughts: I call it "metadata syncing" because the payloads will be quite small, in the form of object IDs and small metadata about those ID-s. When client endpoints retrieve new metadata over this protocol, they will fetch actual object data from an external source based on this metadata. Fetching the "real" object data is out of scope, I'm only talking about metadata syncing here. Using HTTP for transport and JSON for payload container. The question is basically about how to best design the JSON payload schema. I want this to be easy to implement and maintain on the web and across desktop and mobile devices. The best approach feels to be simple timer- or event-based HTTP request/response without any persistent channels. Also, you should not have a PhD to read it, and I want my spec to fit on 2 pages, not 200. Authentication and security are out of scope for this question: assume that the requests are secure and authenticated. The goal is eventual consistency of data on devices, it is not entirely realtime. For example, user can make changes on one device while being offline. When going online again, user would perform "sync" operation to push local changes and retrieve remote changes. Having said that, the protocol should support both of these modes of operation: Starting from scratch on a device, should be able to pull the whole metadata picture "sync as you go". When looking at the data on two devices side by side and making changes, should be easy to push those changes as short individual messages which the other device can receive near-realtime (subject to when it decides to contact server for sync). As a concrete example, you can think of Dropbox (it is not what I'm working on, but it helps to understand the model): on a range of devices, the user can manage a files and folders—move them around, create new ones, remove old ones etc. And in my context the "metadata" would be the file and folder structure, but not the actual file contents. And metadata fields would be something like file/folder name and time of modification (all devices should see the same time of modification). Another example is IMAP. I have not read the protocol, but my goals (minus actual message bodies) are the same. Feels like there are two grand approaches how this is done: transactional messages. Each change in the system is expressed as delta and endpoints communicate with those deltas. Example: DVCS changesets. REST: communicating the object graph as a whole or in part, without worrying so much about the individual atomic changes. What I would like in the answers: Is there anything important I left out above? Constraints, goals? What is some good background reading on this? (I realize this is what many computer science courses talk about at great length and detail... I am hoping to short-circuit it by looking at some crash course or nuggets.) What are some good examples of such protocols that I could model after, or even use out of box? (I mention Dropbox and IMAP above... I should probably read the IMAP RFC.)

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  • Recommended integration mechanism for bi-directional, authenticated, encrypted connection in C clien

    - by rcampbell
    Let me first give an example. Imagine you have a single server running a JVM application. This server keeps a collection of N equations, once for each client: Client #1: 2x Client #2: 1 + y Client #3: z/4 This server includes an HTTP interface so that random visitors can type https://www.acme.com/client/3 int their browsers and see the latest evaluated result of z/4. The tricky part is that either the client or the server may change the variable value at any time, informing the other party immediately. More specifically, Client #3 - a C app - can initially tell the server that z = 20. An hour later that same client informs the server that z = 23. Likewise the server can later inform the client that z = 28. As caf pointed out in the comments, there can be a race condition when values are changed by the client and server simultaneously. The solution would be for both client and server to send the operation performed in their message, which would need to be executed by the other party. To keep things simple, let's limit the operations to (commutative) addition, allowing us to disregard message ordering. For example, the client seeds the server with z = 20: server:z=20, client:z=20 server sends {+3} message (so z=23 locally) & client sends {-2} message (so z=18 locally) at the exact same time server receives {-2} message at some point, adds to his local copy so z=21 client receives {+3} message at some point, adds to his local copy so z=21 As long as all messages are eventually evaluated by both parties, the correct answer will eventually be given to the users of the client and server since we limited ourselves to commutative operations (addition of 3 and -2). This does mean that both client and server can be returning incorrect answers in the time it takes for messages to be exchanged and processed. While undesirable, I believe this is unavoidable. Some possible implementations of this idea include: Open an encrypted, always on TCP socket connection for communication Pros: no additional infrastructure needed, client and server know immediately if there is a problem (disconnect) with the other party, fairly straightforward (except the the encryption), native support from both JVM and C platforms Cons: pretty low-level so you end up writing a lot yourself (protocol, delivery verification, retry-on-failure logic), probably have a lot of firewall headaches during client app installation Asynchronous messaging (ex: ActiveMQ) Pros: transactional, both C & Java integration, free up the client and server apps from needing retry logic or delivery verification, pretty straightforward encryption, easy extensibility via message filters/routers/etc Cons: need additional infrastructure (message server) which must never fail, Database or file system as asynchronous integration point Same pros/cons as above but messier RESTful Web Service Pros: simple, possible reuse of the server's existing REST API, SSL figures out the encryption problem for you (maybe use RSA key a la GitHub for authentication?) Cons: Client now needs to run a C HTTP REST server w/SSL, client and server need retry logic. Axis2 has both a Java and C version, but you may be limited to SOAP. What other techniques should I be evaluating? What real world experiences have you had with these mechanisms? Which do you recommend for this problem and why?

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