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  • Corrupted Laptop - Transfer Data Without My Computer (explorer.exe) Using Command Line

    - by nicorellius
    I have a laptop (Toshiba Satellite) that is pretty messed up. The person this belongs too already replaced it with a new machine. My job is to transfer all her data from this machine to disk so that I can transfer it to her. She doesn't want to lose any data (understandably so). Any operation I attempted (i.e., double clicking on any folder icon, like My Documents, My Computer, etc) resulted din a complete crash. The only good news is that I can actually start and navigate around using the command line. Also, I can access the internet. I have a network, so if I can map the drives I can get this thing figured out (hopefully). Also, I tried a USB drive but I couldn't figure out how to access it from the command line. Two questions (I need to use the command line for these): How would I go about accessing the USB drive and how can I map the shared drives on my network so that I may cd to that directory for use of the copy command?

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  • Big Data – Buzz Words: What is HDFS – Day 8 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned what is MapReduce. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – HDFS. What is HDFS ? HDFS stands for Hadoop Distributed File System and it is a primary storage system used by Hadoop. It provides high performance access to data across Hadoop clusters. It is usually deployed on low-cost commodity hardware. In commodity hardware deployment server failures are very common. Due to the same reason HDFS is built to have high fault tolerance. The data transfer rate between compute nodes in HDFS is very high, which leads to reduced risk of failure. HDFS creates smaller pieces of the big data and distributes it on different nodes. It also copies each smaller piece to multiple times on different nodes. Hence when any node with the data crashes the system is automatically able to use the data from a different node and continue the process. This is the key feature of the HDFS system. Architecture of HDFS The architecture of the HDFS is master/slave architecture. An HDFS cluster always consists of single NameNode. This single NameNode is a master server and it manages the file system as well regulates access to various files. In additional to NameNode there are multiple DataNodes. There is always one DataNode for each data server. In HDFS a big file is split into one or more blocks and those blocks are stored in a set of DataNodes. The primary task of the NameNode is to open, close or rename files and directory and regulate access to the file system, whereas the primary task of the DataNode is read and write to the file systems. DataNode is also responsible for the creation, deletion or replication of the data based on the instruction from NameNode. In reality, NameNode and DataNode are software designed to run on commodity machine build in Java language. Visual Representation of HDFS Architecture Let us understand how HDFS works with the help of the diagram. Client APP or HDFS Client connects to NameSpace as well as DataNode. Client App access to the DataNode is regulated by NameSpace Node. NameSpace Node allows Client App to connect to the DataNode based by allowing the connection to the DataNode directly. A big data file is divided into multiple data blocks (let us assume that those data chunks are A,B,C and D. Client App will later on write data blocks directly to the DataNode. Client App does not have to directly write to all the node. It just has to write to any one of the node and NameNode will decide on which other DataNode it will have to replicate the data. In our example Client App directly writes to DataNode 1 and detained 3. However, data chunks are automatically replicated to other nodes. All the information like in which DataNode which data block is placed is written back to NameNode. High Availability During Disaster Now as multiple DataNode have same data blocks in the case of any DataNode which faces the disaster, the entire process will continue as other DataNode will assume the role to serve the specific data block which was on the failed node. This system provides very high tolerance to disaster and provides high availability. If you notice there is only single NameNode in our architecture. If that node fails our entire Hadoop Application will stop performing as it is a single node where we store all the metadata. As this node is very critical, it is usually replicated on another clustered as well as on another data rack. Though, that replicated node is not operational in architecture, it has all the necessary data to perform the task of the NameNode in the case of the NameNode fails. The entire Hadoop architecture is built to function smoothly even there are node failures or hardware malfunction. It is built on the simple concept that data is so big it is impossible to have come up with a single piece of the hardware which can manage it properly. We need lots of commodity (cheap) hardware to manage our big data and hardware failure is part of the commodity servers. To reduce the impact of hardware failure Hadoop architecture is built to overcome the limitation of the non-functioning hardware. Tomorrow In tomorrow’s blog post we will discuss the importance of the relational database in Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Oracle Data Integration 12c: Perspectives of Industry Experts, Customers and Partners

    - by Irem Radzik
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 As you may have seen from our recent blog posts on Oracle Data Integrator 12c and Oracle GoldenGate 12c, we are very excited to share with you the great new features the 12c release brings to Oracle’s data integration solutions. And, fortunately we are not alone in this sentiment. Since the press announcement October 17th, which incorporates our customers' and experts' testimonials, we have seen positive comments in leading technology publications and social media as well. Here are some examples: In CIO and PCWorld you can find Joab Jackson’s article, Oracle Data Integrator 12c ready for real-time analysis, where wrote about the tight integration between Oracle Data Integrator and Oracle GoldenGate . He noted “Heeding the call from enterprise customers who clamor for more immediacy in their data-driven reports, Oracle has updated its data-integration software portfolio so that it can more rapidly deliver data to data warehouses and analysis applications.” Integration Developer News’ Vance McCarthy wrote the article Oracle Ships ‘Future Proofs’ Integration Tools for Traditional, Cloud, Big Data, Real-Time Projects and mentioned that “Oracle Data Integrator 12c and Oracle GoldenGate 12c sport a wide range of improvements to let devs more easily deliver data integration for cloud, analytics, big data and other new projects that leverage multiple datasets for business.“ InformationWeek’s Doug Henschen gave a great overview to several key features including the new flow-based UI in Oracle Data Integrator. Doug said “Oracle Data Integrator 12c introduces a complete makeover of the job-building experience, while real-time oriented GoldenGate 12c introduces performance gains “. In Database Trends and Applications’ article Oracle Strengthens Data Integration with Release of Oracle Data Integrator 12c and Oracle GoldenGate 12c highlighted the productivity aspect of the new solution with his remarks: “tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c enables developers to leverage Oracle GoldenGate’s low overhead, real-time change data capture completely within the Oracle Data Integrator Studio without additional training”. We are also thrilled about what our customers and partners have to say about our products and the new release. And we are equally excited to share those perspectives with you in our upcoming launch video webcast on November 12th. SolarWorld Industries America’s Senior Database Manager, Russ Toyama will join our executives in our studio in Redwood Shores to discuss GoldenGate’s core benefits and the new release, while Surren Partharb, CTO of Strategic Technology Services for BT, and Mark Rittman, CTO of Rittman Mead, will provide their comments via the interviews conducted in the UK. This interactive panel discussion in the video webcast will unveil the new release with the expertise of our development executives and the great insight from our customers and partners. In addition, our product experts will be available online to answer chat questions. This is really a great opportunity to learn how Oracle's data integration offering has changed the integration and replication technology space with the new release, and established itself as the new leader. If you have not registered for this free event yet, you can do so via this link. We will run the live event at 8am PT/4pm GMT, followed by a replay of the event with live chat for Q&A  at 10am PT/6pm GMT. The replay will be available on-demand for those who register but cannot attend either session on November 12th. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Times New Roman","serif"; mso-fareast-font-family:"Times New Roman";}

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  • Practically expected transfer rates for sdhc class 6

    - by bobobobo
    I went and bought an expensive SanDisk Extreme III SDHC 8GB class 6 chip. However when I dump data from the card to the machine via USB 2.0 cable, its only getting 5.0 MB/second maximum according to Windows 7 disk explorer. It still can take up to 20 minutes to dump the card when its near full. This is so far below the rated 20MB/s transfer speed I can't believe it. Is this normal or might I have a defective chip?

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  • File Transfer with a double SSH login.

    - by Harpal
    I'm have trouble transfering files again from my work PC, which is a linux machine to my home windows PC. My work has changed it so I now need to SSH twice before I can access my PC. So I need to: ssh [email protected] password: xxxxx I then need to do it again. ssh computer_name password: xxxxx I've tried accessing directly via my computers IP but to of no avail. Is there a way I can use pscp or file zilla to ssh twice so I can transfer files?

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  • Level and Player objects - which should contain which?

    - by Thane Brimhall
    I've been working on a several simple games, and I've always come to a decision point where I have to choose whether to have the Level object as an attribute of the Player class or the Player as an attribute of the Level class. I can see arguments for both: The Level should contain the player because it also contains every other entity. In fact it just makes sense this way: "John is in the room." It makes it a bit more difficult to move the player to a new level, however, because then each level has to pass its player object to an upcoming level. On the other hand, it makes programming sense to me to leave the player as the top-level object that is persistent between levels, and the environment changes because the player decides to change his level and location. It becomes very easy to change levels, because all I have to do is replace the level variable on the player. What's the most common practice here? Or better yet, is there a "right" way to architecture this relationship?

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  • Transfer music from iPhone to the computer

    - by hmemcpy
    I'd like to transfer the (non-DRM) music I have on my iPhone to my computer. What application can I use to do that? I found several shareware that didn't really work. EDIT I've removed the Windows tag, so please feel free to add solutions for other OSes.

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  • Maximise network transfer speed of various applications

    - by Alex
    When using nc, scp, wget to transfer files between 2 machines on a dedicated 2Mbps link, I get speeds between 0.5 and 1 Mbps. However, when I use iperf -c 10.0.1.4 -t 20 -P 12 (for example) I can maximise the speed of the link (getting stable 2Mbps). Is there a way to make single stream transfers (such as those done by scp) to utilise all/most of the link? Some kind of tcp settings, or iptables...?

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  • New Big Data Appliance Security Features

    - by mgubar
    The Oracle Big Data Appliance (BDA) is an engineered system for big data processing.  It greatly simplifies the deployment of an optimized Hadoop Cluster – whether that cluster is used for batch or real-time processing.  The vast majority of BDA customers are integrating the appliance with their Oracle Databases and they have certain expectations – especially around security.  Oracle Database customers have benefited from a rich set of security features:  encryption, redaction, data masking, database firewall, label based access control – and much, much more.  They want similar capabilities with their Hadoop cluster.    Unfortunately, Hadoop wasn’t developed with security in mind.  By default, a Hadoop cluster is insecure – the antithesis of an Oracle Database.  Some critical security features have been implemented – but even those capabilities are arduous to setup and configure.  Oracle believes that a key element of an optimized appliance is that its data should be secure.  Therefore, by default the BDA delivers the “AAA of security”: authentication, authorization and auditing. Security Starts at Authentication A successful security strategy is predicated on strong authentication – for both users and software services.  Consider the default configuration for a newly installed Oracle Database; it’s been a long time since you had a legitimate chance at accessing the database using the credentials “system/manager” or “scott/tiger”.  The default Oracle Database policy is to lock accounts thereby restricting access; administrators must consciously grant access to users. Default Authentication in Hadoop By default, a Hadoop cluster fails the authentication test. For example, it is easy for a malicious user to masquerade as any other user on the system.  Consider the following scenario that illustrates how a user can access any data on a Hadoop cluster by masquerading as a more privileged user.  In our scenario, the Hadoop cluster contains sensitive salary information in the file /user/hrdata/salaries.txt.  When logged in as the hr user, you can see the following files.  Notice, we’re using the Hadoop command line utilities for accessing the data: $ hadoop fs -ls /user/hrdataFound 1 items-rw-r--r--   1 oracle supergroup         70 2013-10-31 10:38 /user/hrdata/salaries.txt$ hadoop fs -cat /user/hrdata/salaries.txtTom Brady,11000000Tom Hanks,5000000Bob Smith,250000Oprah,300000000 User DrEvil has access to the cluster – and can see that there is an interesting folder called “hrdata”.  $ hadoop fs -ls /user Found 1 items drwx------   - hr supergroup          0 2013-10-31 10:38 /user/hrdata However, DrEvil cannot view the contents of the folder due to lack of access privileges: $ hadoop fs -ls /user/hrdata ls: Permission denied: user=drevil, access=READ_EXECUTE, inode="/user/hrdata":oracle:supergroup:drwx------ Accessing this data will not be a problem for DrEvil. He knows that the hr user owns the data by looking at the folder’s ACLs. To overcome this challenge, he will simply masquerade as the hr user. On his local machine, he adds the hr user, assigns that user a password, and then accesses the data on the Hadoop cluster: $ sudo useradd hr $ sudo passwd $ su hr $ hadoop fs -cat /user/hrdata/salaries.txt Tom Brady,11000000 Tom Hanks,5000000 Bob Smith,250000 Oprah,300000000 Hadoop has not authenticated the user; it trusts that the identity that has been presented is indeed the hr user. Therefore, sensitive data has been easily compromised. Clearly, the default security policy is inappropriate and dangerous to many organizations storing critical data in HDFS. Big Data Appliance Provides Secure Authentication The BDA provides secure authentication to the Hadoop cluster by default – preventing the type of masquerading described above. It accomplishes this thru Kerberos integration. Figure 1: Kerberos Integration The Key Distribution Center (KDC) is a server that has two components: an authentication server and a ticket granting service. The authentication server validates the identity of the user and service. Once authenticated, a client must request a ticket from the ticket granting service – allowing it to access the BDA’s NameNode, JobTracker, etc. At installation, you simply point the BDA to an external KDC or automatically install a highly available KDC on the BDA itself. Kerberos will then provide strong authentication for not just the end user – but also for important Hadoop services running on the appliance. You can now guarantee that users are who they claim to be – and rogue services (like fake data nodes) are not added to the system. It is common for organizations to want to leverage existing LDAP servers for common user and group management. Kerberos integrates with LDAP servers – allowing the principals and encryption keys to be stored in the common repository. This simplifies the deployment and administration of the secure environment. Authorize Access to Sensitive Data Kerberos-based authentication ensures secure access to the system and the establishment of a trusted identity – a prerequisite for any authorization scheme. Once this identity is established, you need to authorize access to the data. HDFS will authorize access to files using ACLs with the authorization specification applied using classic Linux-style commands like chmod and chown (e.g. hadoop fs -chown oracle:oracle /user/hrdata changes the ownership of the /user/hrdata folder to oracle). Authorization is applied at the user or group level – utilizing group membership found in the Linux environment (i.e. /etc/group) or in the LDAP server. For SQL-based data stores – like Hive and Impala – finer grained access control is required. Access to databases, tables, columns, etc. must be controlled. And, you want to leverage roles to facilitate administration. Apache Sentry is a new project that delivers fine grained access control; both Cloudera and Oracle are the project’s founding members. Sentry satisfies the following three authorization requirements: Secure Authorization:  the ability to control access to data and/or privileges on data for authenticated users. Fine-Grained Authorization:  the ability to give users access to a subset of the data (e.g. column) in a database Role-Based Authorization:  the ability to create/apply template-based privileges based on functional roles. With Sentry, “all”, “select” or “insert” privileges are granted to an object. The descendants of that object automatically inherit that privilege. A collection of privileges across many objects may be aggregated into a role – and users/groups are then assigned that role. This leads to simplified administration of security across the system. Figure 2: Object Hierarchy – granting a privilege on the database object will be inherited by its tables and views. Sentry is currently used by both Hive and Impala – but it is a framework that other data sources can leverage when offering fine-grained authorization. For example, one can expect Sentry to deliver authorization capabilities to Cloudera Search in the near future. Audit Hadoop Cluster Activity Auditing is a critical component to a secure system and is oftentimes required for SOX, PCI and other regulations. The BDA integrates with Oracle Audit Vault and Database Firewall – tracking different types of activity taking place on the cluster: Figure 3: Monitored Hadoop services. At the lowest level, every operation that accesses data in HDFS is captured. The HDFS audit log identifies the user who accessed the file, the time that file was accessed, the type of access (read, write, delete, list, etc.) and whether or not that file access was successful. The other auditing features include: MapReduce:  correlate the MapReduce job that accessed the file Oozie:  describes who ran what as part of a workflow Hive:  captures changes were made to the Hive metadata The audit data is captured in the Audit Vault Server – which integrates audit activity from a variety of sources, adding databases (Oracle, DB2, SQL Server) and operating systems to activity from the BDA. Figure 4: Consolidated audit data across the enterprise.  Once the data is in the Audit Vault server, you can leverage a rich set of prebuilt and custom reports to monitor all the activity in the enterprise. In addition, alerts may be defined to trigger violations of audit policies. Conclusion Security cannot be considered an afterthought in big data deployments. Across most organizations, Hadoop is managing sensitive data that must be protected; it is not simply crunching publicly available information used for search applications. The BDA provides a strong security foundation – ensuring users are only allowed to view authorized data and that data access is audited in a consolidated framework.

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  • How to present a stable data model in a public API that allows internal data structures to be changed without breaking the public view of the data?

    - by Max Palmer
    I am in the process of developing an application that allows users to write C# scripts. These scripts allow users to call selected methods and to access and manipulate data in a document. This works well, however, in the development version, scripts access the document's (internal) data structures directly. This means that if we were to change the internal data model/structure, there is a good chance that someone's script will no longer compile. We obviously want to prevent this breaking change from happening, but still want to allow the user to write sensible C# code (whilst not restricting how we develop our internal data model as a result). We therefore need to decouple our scripting API and its data structures from our internal methods and data structures. We've a few ideas as to how we might allow the user to access a what is effectively a stable public version of the document's internal data*, but I wanted to throw the question out there to someone who might have some real experience of this problem. NB our internal document's data structure is quite complex and it could be quite difficult to wrap. We know we want to expose as little as possible in our public API, especially as once it's out there, it's out there for good. Can anyone help? How do scripting languages / APIs decouple their public API and data structures from their internal data structures? Is there no real alternative to having to write a complex interaction layer? If we need to do this, what's a good approach or pattern for wrapping complex data structures that include nested objects, including collections? I've looked at the API facade pattern, which looks like it's trying to address these kinds of issues, but are there alternatives? *One idea is to build a data facade that is kept stable across versions of our application. The facade exposes a set of facade data objects that are used in the script code. These maintain backwards compatibility and wrap access to our internal document's data model.

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  • JAVA image transfer problem

    - by user579098
    Hi, I have a school assignment, to send a jpg image,split it into groups of 100 bytes, corrupt it, use a CRC check to locate the errors and re-transmit until it eventually is built back into its original form. It's practically ready, however when I check out the new images, they appear with errors.. I would really appreciate if someone could look at my code below and maybe locate this logical mistake as I can't understand what the problem is because everything looks ok :S For the file with all the data needed including photos and error patterns one could download it from this link:http://rapidshare.com/#!download|932tl2|443122762|Data.zip|739 Thanks in advance, Stefan p.s dont forget to change the paths in the code for the image and error files package networks; import java.io.*; // for file reader import java.util.zip.CRC32; // CRC32 IEEE (Ethernet) public class Main { /** * Reads a whole file into an array of bytes. * @param file The file in question. * @return Array of bytes containing file data. * @throws IOException Message contains why it failed. */ public static byte[] readFileArray(File file) throws IOException { InputStream is = new FileInputStream(file); byte[] data=new byte[(int)file.length()]; is.read(data); is.close(); return data; } /** * Writes (or overwrites if exists) a file with data from an array of bytes. * @param file The file in question. * @param data Array of bytes containing the new file data. * @throws IOException Message contains why it failed. */ public static void writeFileArray(File file, byte[] data) throws IOException { OutputStream os = new FileOutputStream(file,false); os.write(data); os.close(); } /** * Converts a long value to an array of bytes. * @param data The target variable. * @return Byte array conversion of data. * @see http://www.daniweb.com/code/snippet216874.html */ public static byte[] toByta(long data) { return new byte[] { (byte)((data >> 56) & 0xff), (byte)((data >> 48) & 0xff), (byte)((data >> 40) & 0xff), (byte)((data >> 32) & 0xff), (byte)((data >> 24) & 0xff), (byte)((data >> 16) & 0xff), (byte)((data >> 8) & 0xff), (byte)((data >> 0) & 0xff), }; } /** * Converts a an array of bytes to long value. * @param data The target variable. * @return Long value conversion of data. * @see http://www.daniweb.com/code/snippet216874.html */ public static long toLong(byte[] data) { if (data == null || data.length != 8) return 0x0; return (long)( // (Below) convert to longs before shift because digits // are lost with ints beyond the 32-bit limit (long)(0xff & data[0]) << 56 | (long)(0xff & data[1]) << 48 | (long)(0xff & data[2]) << 40 | (long)(0xff & data[3]) << 32 | (long)(0xff & data[4]) << 24 | (long)(0xff & data[5]) << 16 | (long)(0xff & data[6]) << 8 | (long)(0xff & data[7]) << 0 ); } public static byte[] nextNoise(){ byte[] result=new byte[100]; // copy a frame's worth of data (or remaining data if it is less than frame length) int read=Math.min(err_data.length-err_pstn, 100); System.arraycopy(err_data, err_pstn, result, 0, read); // if read data is less than frame length, reset position and add remaining data if(read<100){ err_pstn=100-read; System.arraycopy(err_data, 0, result, read, err_pstn); }else // otherwise, increase position err_pstn+=100; // return noise segment return result; } /** * Given some original data, it is purposefully corrupted according to a * second data array (which is read from a file). In pseudocode: * corrupt = original xor corruptor * @param data The original data. * @return The new (corrupted) data. */ public static byte[] corruptData(byte[] data){ // get the next noise sequence byte[] noise = nextNoise(); // finally, xor data with noise and return result for(int i=0; i<100; i++)data[i]^=noise[i]; return data; } /** * Given an array of data, a packet is created. In pseudocode: * frame = corrupt(data) + crc(data) * @param data The original frame data. * @return The resulting frame data. */ public static byte[] buildFrame(byte[] data){ // pack = [data]+crc32([data]) byte[] hash = new byte[8]; // calculate crc32 of data and copy it to byte array CRC32 crc = new CRC32(); crc.update(data); hash=toByta(crc.getValue()); // create a byte array holding the final packet byte[] pack = new byte[data.length+hash.length]; // create the corrupted data byte[] crpt = new byte[data.length]; crpt = corruptData(data); // copy corrupted data into pack System.arraycopy(crpt, 0, pack, 0, crpt.length); // copy hash into pack System.arraycopy(hash, 0, pack, data.length, hash.length); // return pack return pack; } /** * Verifies frame contents. * @param frame The frame data (data+crc32). * @return True if frame is valid, false otherwise. */ public static boolean verifyFrame(byte[] frame){ // allocate hash and data variables byte[] hash=new byte[8]; byte[] data=new byte[frame.length-hash.length]; // read frame into hash and data variables System.arraycopy(frame, frame.length-hash.length, hash, 0, hash.length); System.arraycopy(frame, 0, data, 0, frame.length-hash.length); // get crc32 of data CRC32 crc = new CRC32(); crc.update(data); // compare crc32 of data with crc32 of frame return crc.getValue()==toLong(hash); } /** * Transfers a file through a channel in frames and reconstructs it into a new file. * @param jpg_file File name of target file to transfer. * @param err_file The channel noise file used to simulate corruption. * @param out_file The name of the newly-created file. * @throws IOException */ public static void transferFile(String jpg_file, String err_file, String out_file) throws IOException { // read file data into global variables jpg_data = readFileArray(new File(jpg_file)); err_data = readFileArray(new File(err_file)); err_pstn = 0; // variable that will hold the final (transfered) data byte[] out_data = new byte[jpg_data.length]; // holds the current frame data byte[] frame_orig = new byte[100]; byte[] frame_sent = new byte[100]; // send file in chunks (frames) of 100 bytes for(int i=0; i<Math.ceil(jpg_data.length/100); i++){ // copy jpg data into frame and init first-time switch System.arraycopy(jpg_data, i*100, frame_orig, 0, 100); boolean not_first=false; System.out.print("Packet #"+i+": "); // repeat getting same frame until frame crc matches with frame content do { if(not_first)System.out.print("F"); frame_sent=buildFrame(frame_orig); not_first=true; }while(!verifyFrame(frame_sent)); // usually, you'd constrain this by time to prevent infinite loops (in // case the channel is so wacked up it doesn't get a single packet right) // copy frame to image file System.out.println("S"); System.arraycopy(frame_sent, 0, out_data, i*100, 100); } System.out.println("\nDone."); writeFileArray(new File(out_file),out_data); } // global variables for file data and pointer public static byte[] jpg_data; public static byte[] err_data; public static int err_pstn=0; public static void main(String[] args) throws IOException { // list of jpg files String[] jpg_file={ "C:\\Users\\Stefan\\Desktop\\Data\\Images\\photo1.jpg", "C:\\Users\\Stefan\\Desktop\\Data\\Images\\photo2.jpg", "C:\\Users\\Stefan\\Desktop\\Data\\Images\\photo3.jpg", "C:\\Users\\Stefan\\Desktop\\Data\\Images\\photo4.jpg" }; // list of error patterns String[] err_file={ "C:\\Users\\Stefan\\Desktop\\Data\\Error Pattern\\Error Pattern 1.DAT", "C:\\Users\\Stefan\\Desktop\\Data\\Error Pattern\\Error Pattern 2.DAT", "C:\\Users\\Stefan\\Desktop\\Data\\Error Pattern\\Error Pattern 3.DAT", "C:\\Users\\Stefan\\Desktop\\Data\\Error Pattern\\Error Pattern 4.DAT" }; // loop through all jpg/channel combinations and run tests for(int x=0; x<jpg_file.length; x++){ for(int y=0; y<err_file.length; y++){ System.out.println("Transfering photo"+(x+1)+".jpg using Pattern "+(y+1)+"..."); transferFile(jpg_file[x],err_file[y],jpg_file[x].replace("photo","CH#"+y+"_photo")); } } } }

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  • objective-C : Reset tableview loaded with feltching objects (core data)

    - by the1nz4ne
    hi, i have a tableview application loaded with core data feltching objects and i wanna know if it is possible to reset the table with a simple button. Thanks code to add an object : NSManagedObjectContext *context = [fetchedResultsController managedObjectContext]; NSEntityDescription *entity = [[fetchedResultsController fetchRequest] entity]; NSManagedObject *newManagedObject = [NSEntityDescription insertNewObjectForEntityForName:[entity name] inManagedObjectContext:context]; [newManagedObject setValue:string forKey:@"timeStamp"]; my code to delete (one) object: NSManagedObjectContext *context = [fetchedResultsController managedObjectContext]; [context deleteObject:[fetchedResultsController objectAtIndexPath:indexPath]]; i want a button that reset the tableview and delete everything thanks

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  • The Stub Proto: Not Just For Stub Objects Anymore

    - by user9154181
    One of the great pleasures of programming is to invent something for a narrow purpose, and then to realize that it is a general solution to a broader problem. In hindsight, these things seem perfectly natural and obvious. The stub proto area used to build the core Solaris consolidation has turned out to be one of those things. As discussed in an earlier article, the stub proto area was invented as part of the effort to use stub objects to build the core ON consolidation. Its purpose was merely as a place to hold stub objects. However, we keep finding other uses for it. It turns out that the stub proto should be more properly thought of as an auxiliary place to put things that we would like to put into the proto to help us build the product, but which we do not wish to package or deliver to the end user. Stub objects are one example, but private lint libraries, header files, archives, and relocatable objects, are all examples of things that might profitably go into the stub proto. Without a stub proto, these items were handled in a variety of ad hoc ways: If one part of the workspace needed private header files, libraries, or other such items, it might modify its Makefile to reach up and over to the place in the workspace where those things live and use them from there. There are several problems with this: Each component invents its own approach, meaning that programmers maintaining the system have to invest extra effort to understand what things mean. In the past, this has created makefile ghettos in which only the person who wrote the makefiles feels confident to modify them, while everyone else ignores them. This causes many difficulties and benefits no one. These interdependencies are not obvious to the make, utility, and can lead to races. They are not obvious to the human reader, who may therefore not realize that they exist, and break them. Our policy in ON is not to deliver files into the proto unless those files are intended to be packaged and delivered to the end user. However, sometimes non-shipping files were copied into the proto anyway, causing a different set of problems: It requires a long list of exceptions to silence our normal unused proto item error checking. In the past, we have accidentally shipped files that we did not intend to deliver to the end user. Mixing cruft with valuable items makes it hard to discern which is which. The stub proto area offers a convenient and robust solution. Files needed to build the workspace that are not delivered to the end user can instead be installed into the stub proto. No special exceptions or custom make rules are needed, and the intent is always clear. We are already accessing some private lint libraries and compilation symlinks in this manner. Ultimately, I'd like to see all of the files in the proto that have a packaging exception delivered to the stub proto instead, and for the elimination of all existing special case makefile rules. This would include shared objects, header files, and lint libraries. I don't expect this to happen overnight — it will be a long term case by case project, but the overall trend is clear. The Stub Proto, -z assert_deflib, And The End Of Accidental System Object Linking We recently used the stub proto to solve an annoying build issue that goes back to the earliest days of Solaris: How to ensure that we're linking to the OS bits we're building instead of to those from the running system. The Solaris product is made up of objects and files from a number of different consolidations, each of which is built separately from the others from an independent code base called a gate. The core Solaris OS consolidation is ON, which stands for "Operating System and Networking". You will frequently also see ON called the OSnet. There are consolidations for X11 graphics, the desktop environment, open source utilities, compilers and development tools, and many others. The collection of consolidations that make up Solaris is known as the "Wad Of Stuff", usually referred to simply as the WOS. None of these consolidations is self contained. Even the core ON consolidation has some dependencies on libraries that come from other consolidations. The build server used to build the OSnet must be running a relatively recent version of Solaris, which means that its objects will be very similar to the new ones being built. However, it is necessarily true that the build system objects will always be a little behind, and that incompatible differences may exist. The objects built by the OSnet link to other objects. Some of these dependencies come from the OSnet, while others come from other consolidations. The objects from other consolidations are provided by the standard library directories on the build system (/lib, /usr/lib). The objects from the OSnet itself are supposed to come from the proto areas in the workspace, and not from the build server. In order to achieve this, we make use of the -L command line option to the link-editor. The link-editor finds dependencies by looking in the directories specified by the caller using the -L command line option. If the desired dependency is not found in one of these locations, ld will then fall back to looking at the default locations (/lib, /usr/lib). In order to use OSnet objects from the workspace instead of the system, while still accessing non-OSnet objects from the system, our Makefiles set -L link-editor options that point at the workspace proto areas. In general, this works well and dependencies are found in the right places. However, there have always been failures: Building objects in the wrong order might mean that an OSnet dependency hasn't been built before an object that needs it. If so, the dependency will not be seen in the proto, and the link-editor will silently fall back to the one on the build server. Errors in the makefiles can wipe out the -L options that our top level makefiles establish to cause ld to look at the workspace proto first. In this case, all objects will be found on the build server. These failures were rarely if ever caught. As I mentioned earlier, the objects on the build server are generally quite close to the objects built in the workspace. If they offer compatible linking interfaces, then the objects that link to them will behave properly, and no issue will ever be seen. However, if they do not offer compatible linking interfaces, the failure modes can be puzzling and hard to pin down. Either way, there won't be a compile-time warning or error. The advent of the stub proto eliminated the first type of failure. With stub objects, there is no dependency ordering, and the necessary stub object dependency will always be in place for any OSnet object that needs it. However, makefile errors do still occur, and so, the second form of error was still possible. While working on the stub object project, we realized that the stub proto was also the key to solving the second form of failure caused by makefile errors: Due to the way we set the -L options to point at our workspace proto areas, any valid object from the OSnet should be found via a path specified by -L, and not from the default locations (/lib, /usr/lib). Any OSnet object found via the default locations means that we've linked to the build server, which is an error we'd like to catch. Non-OSnet objects don't exist in the proto areas, and so are found via the default paths. However, if we were to create a symlink in the stub proto pointing at each non-OSnet dependency that we require, then the non-OSnet objects would also be found via the paths specified by -L, and not from the link-editor defaults. Given the above, we should not find any dependency objects from the link-editor defaults. Any dependency found via the link-editor defaults means that we have a Makefile error, and that we are linking to the build server inappropriately. All we need to make use of this fact is a linker option to produce a warning when it happens. Although warnings are nice, we in the OSnet have a zero tolerance policy for build noise. The -z fatal-warnings option that was recently introduced with -z guidance can be used to turn the warnings into fatal build errors, forcing the programmer to fix them. This was too easy to resist. I integrated 7021198 ld option to warn when link accesses a library via default path PSARC/2011/068 ld -z assert-deflib option into snv_161 (February 2011), shortly after the stub proto was introduced into ON. This putback introduced the -z assert-deflib option to the link-editor: -z assert-deflib=[libname] Enables warning messages for libraries specified with the -l command line option that are found by examining the default search paths provided by the link-editor. If a libname value is provided, the default library warning feature is enabled, and the specified library is added to a list of libraries for which no warnings will be issued. Multiple -z assert-deflib options can be specified in order to specify multiple libraries for which warnings should not be issued. The libname value should be the name of the library file, as found by the link-editor, without any path components. For example, the following enables default library warnings, and excludes the standard C library. ld ... -z assert-deflib=libc.so ... -z assert-deflib is a specialized option, primarily of interest in build environments where multiple objects with the same name exist and tight control over the library used is required. If is not intended for general use. Note that the definition of -z assert-deflib allows for exceptions to be specified as arguments to the option. In general, the idea of using a symlink from the stub proto is superior because it does not clutter up the link command with a long list of objects. When building the OSnet, we usually use the plain from of -z deflib, and make symlinks for the non-OSnet dependencies. The exception to this are dependencies supplied by the compiler itself, which are usually found at whatever arbitrary location the compiler happens to be installed at. To handle these special cases, the command line version works better. Following the integration of the link-editor change, I made use of -z assert-deflib in OSnet builds with 7021896 Prevent OSnet from accidentally linking to build system which integrated into snv_162 (March 2011). Turning on -z assert-deflib exposed between 10 and 20 existing errors in our Makefiles, which were all fixed in the same putback. The errors we found in our Makefiles underscore how difficult they can be prevent without an automatic system in place to catch them. Conclusions The stub proto is proving to be a generally useful construct for ON builds that goes beyond serving as a place to hold stub objects. Although invented to hold stub objects, it has already allowed us to simplify a number of previously difficult situations in our makefiles and builds. I expect that we'll find uses for it beyond those described here as we go forward.

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  • Why Cornell University Chose Oracle Data Masking

    - by Troy Kitch
    One of the eight Ivy League schools, Cornell University found itself in the unfortunate position of having to inform over 45,000 University community members that their personal information had been breached when a laptop was stolen. To ensure this wouldn’t happen again, Cornell took steps to ensure that data used for non-production purposes is de-identified with Oracle Data Masking. A recent podcast highlights why organizations like Cornell are choosing Oracle Data Masking to irreversibly de-identify production data for use in non-production environments. Organizations often copy production data, that contains sensitive information, into non-production environments so they can test applications and systems using “real world” information. Data in non-production has increasingly become a target of cyber criminals and can be lost or stolen due to weak security controls and unmonitored access. Similar to production environments, data breaches in non-production environments can cost millions of dollars to remediate and cause irreparable harm to reputation and brand. Cornell’s applications and databases help carry out the administrative and academic mission of the university. They are running Oracle PeopleSoft Campus Solutions that include highly sensitive faculty, student, alumni, and prospective student data. This data is supported and accessed by a diverse set of developers and functional staff distributed across the university. Several years ago, Cornell experienced a data breach when an employee’s laptop was stolen.  Centrally stored backup information indicated there was sensitive data on the laptop. With no way of knowing what the criminal intended, the university had to spend significant resources reviewing data, setting up service centers to handle constituent concerns, and provide free credit checks and identity theft protection services—all of which cost money and took time away from other projects. To avoid this issue in the future Cornell came up with several options; one of which was to sanitize the testing and training environments. “The project management team was brought in and they developed a project plan and implementation schedule; part of which was to evaluate competing products in the market-space and figure out which one would work best for us.  In the end we chose Oracle’s solution based on its architecture and its functionality.” – Tony Damiani, Database Administration and Business Intelligence, Cornell University The key goals of the project were to mask the elements that were identifiable as sensitive in a consistent and efficient manner, but still support all the previous activities in the non-production environments. Tony concludes,  “What we saw was a very minimal impact on performance. The masking process added an additional three hours to our refresh window, but it was well worth that time to secure the environment and remove the sensitive data. I think some other key points you can keep in mind here is that there was zero impact on the production environment. Oracle Data Masking works in non-production environments only. Additionally, the risk of exposure has been significantly reduced and the impact to business was minimal.” With Oracle Data Masking organizations like Cornell can: Make application data securely available in non-production environments Prevent application developers and testers from seeing production data Use an extensible template library and policies for data masking automation Gain the benefits of referential integrity so that applications continue to work Listen to the podcast to hear the complete interview.  Learn more about Oracle Data Masking by registering to watch this SANS Institute Webcast and view this short demo.

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  • Removing Barriers to Create Effective Data Models

    After years of creating and maintaining data models, I have started to notice common barriers that decrease the accuracy and usefulness of models. In my opinion, the main causes of these barriers are the lack of knowledge and communication from within a company. The lack of knowledge in regards to data models or data modeling can take many forms. Company Culture Knowledge Whether documented or undocumented, existing business rules of a company can affect how data is modeled. For example, if a company only allows 1 assigned person per customer to be able to manipulate a customer’s record then then a data model that includes an associated table that joins customers and employee’s would be unneeded because that would allow for the possibility of multiple employees to handle a customer because of the potential for a many to many relationship between Customers and Employees. Technical Knowledge Depending on the data modeler’s proficiency in modeling data they can inadvertently cause issues and/or complications with a design without even noticing. It is important that companies share data modeling responsibilities so that the models are developed from multiple perspectives of a system, company and the original problem.  In addition, the tools that a company selects to create data models can also affect the accuracy of the model if designer are not familiar with the tools or the tools are too complex to use for the designer. Existing System Knowledge In order for a data modeler to model data for an existing system so that new changes can be applied to a system then they need to at least know the basic concepts of a system so that they can work within it. This will promote reusability of data and prevent the chance of duplicating data. Project Knowledge This should be pretty obvious, but it is very hard to create an accurate data model without knowing what data needs to be modeled. I have always found it strange that I have been asked to start modeling data prior to a client formalizing any requirements. Usually when this happens I have to make several iterations to a model, and the client still does not know exactly what they want.  In addition additional issues can arise when certain stakeholders of a project are not consulted prior to the design or after the project is over because it can cause miss understandings and confusion by the end user as well as possibly not solving the original problem for which a project is intended to solve. One common thread between each type of knowledge is that they can all be avoided through the use of good communication. For example, if a modeler is new to a company then they should ask older employees about any business specific rules that may be documented or undocumented that must be applied to projects in general. Furthermore, if a modeler is not really familiar with a specific data modeling software then they need to speak up and ask for help form other employees or their manager. This will not only help the modeler in the project, but also help them in future projects that they do for the company. Additionally, if a project is not clearly defined prior to a data modeler being assigned the modeling project then it is their responsibility to communicate with the other stakeholders to clarify any part of a project that is unclear so that the data model that is created is accurately aligned with a project.

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  • Folder/File permission transfer between alike file structure

    - by Tyler Benson
    So my company has recently upgraded to a new SAN but the person who copied all the data over must have done a drag n' drop or basic copy to move everything. Apparently Xcopy is not something he cared to use. So now I am left with the task of duplicating all the permissions over. The structure has changed a bit ( as in more files/folders have been added) but for the most part has been stayed unchanged. I'm looking for suggestions to help automate this process. Can I use XCopy to transfer ONLY permissions to one tree from another? Would i just ignore any folders/permissions that don't line up correctly? Thanks a ton in advance, Tyler

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  • Transfer Books from Mac to Kindle App on the Nexus 7

    - by AJ.
    I have some e-books that I've downloaded from Project Gutenberg and some other sources to my MBP. They are all DRM free. Excluding e-mail them to my Kindle as a personal document as a method (the total size is more than 5 GB, the space provided by Amazon), is there any way to transfer these books to my Kindle App on my Nexus 7 (Android Tablet). I have the Kindle App version 3.1.7 I've already seen the question Can I sync books I didn't buy from Amazon via Kindle app? but that is not the answer I'm looking for. Thanks

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  • Best way to transfer files across unstable LAN?

    - by JamesTheAwesomeDude
    This is very similar to Question 326211, but in this case, the LAN is an unstable Wi-Fi connection. I need to transfer about 11 GiB of files between two computers, both running Linux (although one may be rebooted into Windows.) Their connection is both slow and unstable (due to Linux's awful Wi-Fi support,) but removable media (such as a flash drive or external hard drive) is not an option at this time. Right now, I'm slowly transferring the files, one by one, across SFTP, but I have to reconnect each computer approximately every 90 seconds, and the computers are not very close to each other, so this is not feasible. This is not a duplicate of Question 30186; that one specifically concerns Windows 7, and all the proposed solutions involve closed-source, Windows-only programs (which are all spyware IMHO, and are all off the table even if I trusted them - one of the computers is Linux-only.)

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