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250-250 - Veritas Storage Foundation 5.0 Administration for UNIX - Dump Information

Vendor : Symantec
Exam Code : 250-250
Exam Name : Veritas Storage Foundation 5.0 Administration for UNIX
Questions and Answers : 140 Q & A
Updated On : December 12, 2017
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250-250 Questions and Answers

250-250


vxdg -g datadg rmdisk datadg01 The status of the disk is _.


  1. Online

  2. Invalid

  3. Foreign

  4. Offline


Answer: A


QUESTION: 112

What must you do to rename the testdg disk group to engdg from the command line?


  1. Destroy the disk group and then re-create the disk group using the new name.

  2. Use the vxdg change command, which performs a deport and an import in a single step.

  3. Use vxdg deport followed by vxdg import; the volumes are automatically started in the disk group after the import.

  4. Use vxdg deport followed by vxdg import and then manually start volumes in the disk group by using the vxvol command.


Answer: D


QUESTION: 113

Which statements are true about adding a mirror to a volume? (Choose three.)


  1. Only concatenated or striped volumes can be mirrored.

  2. By default, a mirror is created with the same layout as the original volume.

  3. A volume can have up to 64 mirrors.

  4. Disks with mirrors can be in different disk groups.

  5. Each mirror must reside on a separate LUN.


Answer: A, B, E


QUESTION: 114

What are the different operating modes of the vxconfigd daemon? (Choose three.)


  1. Enabled

  2. Faulted

  3. Stopped

  4. Booted

  5. Disabled


Answer: A, D, E


QUESTION: 115

Which disk group names are reserved system-wide? (Choose two.)


  1. rootdg

  2. vmdg

  3. nodg

  4. defaultdg

  5. systemdg


Answer: C, D


QUESTION: 116

What are the options when you deport a disk group? (Choose two.)


  1. Rename

  2. Simple

  3. New version

  4. New host

  5. Temporary


Answer: A, D


QUESTION: 117

Which vxprint parameters display subvolume information?


  1. -sv

  2. -r

  3. -rf

  4. -l


Answer: B


QUESTION: 118

Which command is used to restart the configuration daemon with debugging turned on at its highest level?


  1. vxconfigd -k -x 9


  2. vxconfigd -k -d 9

  3. vxconfigd -d 9

  4. vxconfigd -r -d 9


Answer: A


QUESTION: 119

Which vxassist command option changes the layout of a layered volume to a non-layered volume?


  1. Mirror

  2. Relayout

  3. Convert

  4. Layered


Answer: C


QUESTION: 120

Which conversion option is used to convert a RAID-0+1 volume to a layered volume?


  1. Mirror-stripe to stripe-mirror

  2. Stripe-mirror to mirror-stripe

  3. Mirror-concatenate to concatenate-mirror

  4. Concatenate-mirror to mirror-concatenate


Answer: A


Symantec 250-250 Exam (Veritas Storage Foundation 5.0 Administration for UNIX) Detailed Information

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Symantec receives candidate exam results daily via file transfers from Pearson VUE to CertTracker Be sure you keep your personal information in your CertTracker profile up-to-date so that you receive proper credit for exams passed and certifications earned.
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Passing scores vary by exam. For more information on specific certifications in each category, please see the certification exam details within your selected product solution training path.
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If you do not pass an exam on your first attempt, you must wait at least 3 days (72 hours) before a second attempt. If you do not pass an exam on your second attempt, then you must wait at least 2 weeks (14 days) between each additional attempt. If you need to retake an exam that you have already passed in order to fulfill a certification track requirement, you may do so after 3 months. The same cost applies whether you take an exam once or many times.
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Certification requirements, sample exams, exam objectives, recommended training and registration is available for each certification and corresponding exam. For more information on specific certifications in each category, please see the certification exam details within your selected product solution training path.
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Exams are developed for the current version of the Symantec product release at the time of development. Exams may be updated after significant new versions are released. New exams may not always correspond to the software release schedule.
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For more information on specific certifications in each category, please see the certification exam details within your selected product solution training path.
Are practice or sample exams available?
Sample exams are available. Each sample exam consists of multiple-choice items. Some items may have a supporting exhibit which you will be directed to view before answering the item. The sample exams are not timed, however, you should attempt to complete them as quickly as you can. Certification requirements, sample exams, exam objectives, study guides, recommended training, and registration is available for each certification and corresponding exam. For more information on specific certifications in each category, please see the certification exam details within your selected product solution training path.
Why does Symantec list a range of questions for exams?
Symantec regularly conducts statistical analyses of certification exam results for exam maintenance purposes. In doing so, Symantec publishes a range of questions per exam to account for “unscored” questions. In order to ensure the value of the Symantec certification program, Symantec routinely updates exams with new questions on an unannounced basis. Those new questions are initially delivered as “unscored” so that Symantec can evaluate the performance in the field/on the released exam. The “unscored” questions do not count towards your passing score and additional time is already incorporated into the total exam duration to answer these questions.
Symantec also regularly updates exam questions where the actual number of questions per exam may vary from time to time as these unannounced updates occur.
How are the exams developed?
Symantec end users, both internally and in the field, are studied to define the job performance requirements. The results determine the minimum level of competence required for the defined job performance and is tested in the exams. Symantec follows industry standards for “high stakes” exam development.
How are passing scores established?
Although it is intuitive to think that an appropriate passing score for an examination should be 70 or 75 percent correct based on personal experiences taking classroom tests, these arbitrary values may not reflect the performance level expected of the “minimally qualified candidate” given the difficulty of the test. For example, if the examination is very easy, a passing score of 70 may be too low. However, if the examination is very difficult, this same value may be too high.
Establishing passing scores requires the application of systematic procedures that consider the defined performance level definition of the “minimally qualified candidate” and the difficulty of the examination. Before the final passing scores are established, they are evaluated to ensure that the available validity evidence supports their use for the intended purpose of distinguishing the “minimally qualified candidates” from those who are not yet qualified. This systematic method is used to establish and maintain the fairness, validity and reliability of exams.
In order to ensure the value of the Symantec certification program, Symantec routinely updates exams with new questions. In these cases the passing percentage could change per exam from time to time as these unannounced updates occur
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    Evaluating the Effect of Online Data Compression on the Disk Cache of a Mass Storage System

    1 Evaluating the Effect of Online Data Compression on the Disk Cache of a Mass Storage System Odysseas I. Pentakalos and Yelena Yesha Computer Science Department University of Maryland Baltimore County Baltimore, Maryland and Center of Excellence in Space Data and Information Sciences Goddard Space Flight Center Greenbelt, Maryland A trace driven simulation of the disk cache of a mass storage system was used to evaluate the effect of an online compression algorithm on various performance measures. Traces from the system at NASA s Center for Computational Sciences were used to run the simulation and disk cache hit ratios, number of files and bytes migrating to tertiary storage were measured. The measurements were performed for both an LRU and a size based migration algorithm. In addition to seeing the effect of online data compression on the disk cache performance measure, the simulation provided insight into thecharacteristics of the interactive references, suggesting that hint based prefetching algorithms are the only alternative for any future improvements to the disk cache hit ratio. I. Introduction Mass storage systems are used in research environments for storing data generated by scientific simulations and satellite observations in amounts on the order of terabytes. The cost of storage devices of that capacity is still very high while the rate of increase in disk space requirements by the users grows continuously. This problem is especially evident in scientific research centers where enormous amounts of data are generated on a daily basis which must be archived so that they can be analyzed at a later time [1],[2]. In this study the actual system under consideration is the Unitree Mass Storage System (UMSS) used at NASA s Center for Computational Sciences (NCCS). The system administrators are experiencing a situation where they constantly need to purchase additional storage devices which are filled to capacity in a decreasing amount of time. The main resource whose utilization must be optimized in this case is storage capacity. Removing the redundancy in the data stored in the file system, by inserting an online compressiondecompression module, is one method of increasing the effective capacity of the system without the addition of expensive hardware devices. After considering various alternative locations in the system at which the compression algorithm could be placed we determined that the user interface would be the best choice. Some of the advantages of placing compression at the user interface are: a) does not impose an additional load on the storage servers CPU, b) reduces the amount of data that flows

    2 through the network, and c) does not require modifications to the Unitree code. To evaluate the performance of compression on the specific data stored at NCCS, the ftp clients were modified to implement Ziv-Lempel and LZW compression transparently [3],[4],[5]. Sequential and pipelined implementations were tested against two sets of files and the performance of each implementation was compared based on file compression ratio and compression rate. An earlier paper describes the implementations and the results in detail [6]. In this study we examine the effect of compression on the disk cache of the mass storage system. A simulation is used to determine the effect of compressing data on the hit-ratio of the disk cache, the number of migrations of files from the disk cache to robotic storage, and the total number of bytes migrating to robotic storage. We also look at two different migration algorithms and their effect on the hit ratio and the file migrations. Section II gives a description of the system under consideration and reviews terminology that will be used throughout the rest of the paper. Section III describes the simulation used in this study. Section IV describes the simulations performed and analyzes the results. Section V concludes the paper and discusses future work. II. System Overview The UMSS is a hierarchical mass storage management system which runs as a centralized application program on top of the Unix operating system and manages a hierarchical mass storage file system. The specific installation offers three levels in the storage hierarchy. Figure 1 shows the typical storage pyramid provided by most hierarchical mass storage systems.at the higher level it provides a disk array, with a total capacity of 150 Gbs, which serves mainly as a cache for the lower levels. The second level has a capacity of 4.8 terabytes provided by four near-line robotic tape storage units. The third level is the off-line storage vault which has the slowest transfer rate serving as the long-term repository. Fig.1 Hierachical Storage Pyramid Users access files stored in the UMSS using the ftp protocol from their local workstations via a local area network. In addition to the ftp protocol, UMSS also provides an NFS interface to the file system but due to performance and security reasons the NFS protocol is not used by many installations including the one at NCCS. The UMSS was designed in a modular fashion in order to make possible its distribution over multiple host machines. Figure 2 shows a block diagram of the UMSS components [7]. Each of the components shown in figure 2 is represented by one or more independent daemon processes and is responsible for certain tasks.

    3 cache, if they are not already there, and then are transferred to the user. Likewise, any files stored into the UMSS are first stored in the disk cache and then they are moved to a lower level of the hierarchy through migration. In an earlier paper we investigated the effectiveness of an online data compression algorithm placed at the user interface of a mass storage system [6]. For a sequential implementation the following inequality describes the trade-off in time of compressing the data online. Fig 2. UMSS Block Diagram The Name Server resolves string file names used by the users, into unique integer identifiers, used internally by all the other components of the UMSS. The Disk Server keeps track of the files stored in the disk cache, providing the view of a Unix file system to the user. The Disk Mover is responsible for all transfers to and from the disk cache. The Migration Server controls the migration of files from the disk cache to lower levels in the disk hierarchy to ensure that the disk cache always has sufficient free space to operate efficiently. The Tape Server keeps track of the files stored in the tape storage units whether online or off-line. The Tape Mover performs all file transfers to and from a tape device. The physical device manager is responsible for managing the tape mounts, scheduling them in an order which maximizes the utilization of the system resources. Finally, the Physical Volume Repository is responsible for mounting and dismounting both automated online and off-line storage physical volumes [8]. Any files retrieved from the UMSS are first placed in the disk S S S( 1 rc) > + Rc rc > + (1) Rc < rcrc where S is the size of the file, R t is the file transfer rate, R c is the compression rate and r c is the compression ratio normalized to the range [0,1]. The left hand side is the time it takes to transfer the file without compression and the left side with compression. If the compression rate of the compression algorithm used is faster than the transfer rate of the network between the client and the server then the embedded compression increases the effective capacity of the storage server at no additional cost. Note that by cost here we mean the amount of time it takes to store a file into the mass storage system. If this inequality does not hold, the online compression algorithm increases the effective capacity of the system at the expense of added time when storing the file. The above inequality applies only to the sequential implementation. Assuming that the communication time between the parent and child processes is negligible we can derive a similar relation for the

    4 pipelined implementation as shown in inequality 2. S S S( 1 rc) > max{, } (2) Rc The total time of the pipeline is bounded by the maximum of each of its components. Which of the two components prevails will depend on the particular client making the request and on the network topology. If the client is connected locally relative to the server but is a slow machine then the compression component will prevail whereas on a fast machine which is a few hops from the server the transmission component will prevail. III. Disk Cache Simulation A trace-driven simulation of the disk cache was used to ascertain the effect on the hit ratio and on the migration of files caused by file compression and migration algorithm. A discrete event simulator was developed using the ftp request traces to drive the simulation.the disk cache size was varied from 150GB, which is the actual disk cache size at the NCCS site, to 250GB. Initially the cache was assumed to be empty. The disk cache was represented by a doubly linked list of structures which described each file entry. The information stored for each file were a unique file identifier, the file size, a timestamp of the time the file entered the disk cache, and an indicator of whether the file is stored in the disk cache or in the lower levels of the hierarchy. Put requests were placed in the disk cache. If the file already resided in the cache or lower in the hierarchy the operation was processed as an update, ensuring that only one copy of the file existed in the entire mass storage system. For get requests, if the file existed in the disk cache then the request was considered a hit. If the file existed lower in the hierarchy it was staged in the disk cache. If the file requested did not exist in the hierarchy, it was processed as if it was in the lower levels of the hierarchy and a new entry was created for the file in the disk cache. Migration in simulated time was performed using a high water mark as in the UCFM. If the amount of free space in the cache went below the high water mark of 75 the total disk cache capacity, files were migrated to the lower levels of the hierarchy to create more space. Two different migration algorithms were tested. The first one, was LRU based, selecting files to migrate which had resided in the cache the longest without being referenced. The second algorithm was based on the file size, migrating larger files first. Since it would be impractical to collect the compression ratios for each of the files in the mass storage system each simulation run used a fixed compression ratio. The simulation was run for various compression ratios ranging from 0% to 60% compression. IV. Results The ftp interactive request logs for a period of three months were used to run the simulation. The total number of references in that three month period was approximately 106,000. The references from the first two months were used for bringing the disk cache to a warm state. Then the number of hits, the hit ratio, the number of files migrating to tertiary storage, and the total number of bytes migrated were measured for fixed values of compression ratio.the simulation was run

    5 also for two different migration algorithms. The first migration algorithm, which selected files to migrate if they had resided on the disk cache the longest without being referenced, will be referred to as the LRU based algorithm. The second algorithm which selected files to migrate based on their file size will be referred to as the Size based algorithm. The hit ratio was computed as the number of hits per day over the number of get requests on that specific day. One important observation that was made about the reference patterns used in this mass storage system was that the requests do not exhibit significant temporal locality. Users do not tend to re-use their files very frequently as in a typical file system. This implies that this specific mass storage system is used more as an archive than as a typical file system. Since the working set of the get request stream continuously changes, only low hit ratios are possible regardless of size increases to the disk cache. In order to be able to compare the hit ratios measured with some sort of an optimal hit ratio we run the simulation on the same trace data setting the compression ratio to a value very close to zero. This allowed all the files to fit within the disk cache, imitating a disk cache of an enormous size, generating no migrations. This experiment was used to generate the optimal (OPT) disk cache hit ratios. The same method was used to compute the hit ratio of this cache as in the other cases. Table I summarizes the effect of compression on the number of hits for each of the experiments. The table is divided in three major column groups for each of the migration algorithms. The first column group shows the results for the LRU based migration algorithm, the second column group for the Size based migration algorithm, and the last column shows the results for the OPT disk cache. The first two column groups consist of three columns, one for each of three different compression ratios attempted. Comparing the results from the two migration algorithms against the results under OPT we see that the number of hits for both algorithms are very close to the optimal. Compression does not affect the hit ratio very much and this is because the disk cache is large enough to support the hits in the reference patterns. It should be noted that the LRU based algorithm exhibits the inclusion property as expected since the number of hits is non-decreasing with increases in the disk cache size. On the other hand, the size based algorithm in certain cases decreases with a larger effective disk cache size. The hit ratios were also plotted in figure 3 for various compression ratios. The plot on the top shows the hit ratio variation with respect to the compression ratio for the size based migration algorithm and the bottom plot shows the variation for the LRU based migration algorithm. It is apparent from these figures that size based migration provides higher hit ratios than the LRU based algorithm. The variation in compression ratio does not have significant effect on the hit ratio and the reason for this is the same as discussed in the previous paragraph. This implies that adding additional disks to the disk cache will not have any effect on the hit ratio based on the references analyzed. Also any further effort in improving the hit ratio by varying the migration algorithm will not generate any significant improvement on the hit ratio. The only possible method of increasing the hit ratio would be to develop a prefetching

    6 LRU Based Size Based r c OPT The second part of the simulation analysis algorithm that is based on hints provided by the user. focused on the migrations. Since migration involves the use of tape drives from the robotic silos it is an expensive operation. Thus, reducing the number of migrations or the total number of bytes migrating to the tape will improve the mass storage system s performance. Figure 4 shows the number of files migrating versus compression ratio for the two migration algorithms. The LRU based algorithm maintains a consistent number of migrations and tends to smooth the migration operations over time. It appears that the effect of file compression is minimal. Looking at the peaks in the LRU based algorithm it appears that compression simply shifts the migration effects but does not reduce their number. The size based migration algorithm decreases significantly the number of migrations but it has the negative effect of generating on certain days tremendous migration traffic. Analyzing the file sizes Fig. 3. Hit-Ratio versus Compression Ratio for both get and put requests we found that the mean file size of files stored in the storage system is an order of magnitude larger than the mean file size of files

    7 retrieved. Since the size based algorithm removes larger files first, eventually it runs out of large files and it has to remove a huge number of small files to free space in the disk cache. from the disk cache affects the overhead time while reducing the number of bytes migrating to robotic storage reduces the data transfer time. V. Conclusion Fig. 4. Number of Migrations versus Compression Ratio Figure 5 shows the number of bytes migrating to robotic storage for various compression ratios. It is apparent that for both migration algorithms the higher compression ratio provides significant reduction in the number of bytes that need to migrate. The size based migration algorithm provides better performance throughout the simulation period. The time it takes the system to process a migration involves an overhead time and a data transfer time. The overhead time consists of mounting the tape on a tape drive, a seek time to place the tape drive heads at the proper location, a rewind time after the data have been written, and an unmount time. Reducing the number of migrations We evaluated the performance of an online compression algorithm on the disk cache of a mass storage system. A trace driven simulation of the disk cache was used for the evaluation. The traces used to drive the simulator were collected from the ftp logs of the system. The simulation was configured to match the disk space and migration algorithm of the system at NCCS. The effect of compression was simulated by uniformly reducing the file size of the get and put requests. Various compression ratios were used in the simulation. The simulation also evaluated two different migration algorithms, specifically an LRU based and a size based algorithm. One important observation that was made about the references at this mass storage

    8 system was that the working set continuously changes. This implies that the disk cache hit ratio cannot be improved significantly by increasing the disk cache size since get operations are usually to files that were stored in the mass storage system a very long time in the past. This effect was evident by comparing the two migration algorithms against a disk cache which was large enough to store all files stored during the three month evaluation period. As a result both algorithms attained hit ratios very close to the optimal hit ratios of the huge cache. Comparing the two migration algorithms we found that the size based algorithm decreases the total number of bytes migrating to tertiary storage at the expense of causing occasional peaks in the number of files migrating. Both algorithms were not affected by the compression ratio due to the fact that the disk cache is of large enough size to cover the intereference pattern of the requests. Future work will focus on evaluating various prefetching algorithms.the current simulation suggested that only the use of user hints and an appropriate prefetching algorithm can improve the hit ratio of this system. The use of transparent informed prefetching could be applied to improve the hit ratio of the disk cache by exploiting application level hints about future file accesses [9]. Another area of future research is the implementation and evaluation of migration algorithms based on a combination of file size and cache residency time as described in [10],[11]. This simulation analysis showed that size based migration reduces the number of bytes that migrate to tertiary storage but occasionally it produces a large number of migration loads. By using a migration algorithm based on the space time product we expect that the migration peaks will disappear, while maintaining the lower number of bytes migrating. Acknowledgements We would like to thank Adina Tarshish, Ellen Salmon and George Rumney from NASA s Center for Computational Sciences at Goddard Space Flight Center for providing the ftp traces and the NCCS file set used for testing our ideas. REFERENCES [1] Randy H. Katz, Thomas E. Anderson, John K. Ousterhout, and David A. Patterson, Robo-line Storage: Low Latency, High Capacity Storage Systems over Geographically Distributed Networks, Tech. Rep. U2K-91-3, University of California, Berkeley, March [2] Ethan L. Miller and Randy H. Katz, An Analysis of File Migration in a Unix Supercomputing Environment,Tech. Rep. UCBCSD , University of California, Berkeley, March [3] J. Ziv and A. Lempel, A Universal Algorithm for Sequential Data Compression, IEEE Transactions on Information Theory, vol. 23, no. 3, pp , [4] Debra A. Lelewer and Daniel S. Hirschberg, Data Compression, ACM Computing Surveys, vol. 19, no. 3, pp , September [5] Terry A. Welch, A Technique for High-Performance Data Compression, IEEE Computer, vol. 17, no. 6, pp. 8-19, June [6] Odysseas I. Pentakalos and Yelena Yesha, Online Data Compression for

    9 Mass Storage File Systems, Tech. Rep. TR-CS-95-05, University of Maryland Baltimore County, July [7] Adina Tarshish and Ellen Salmon, The Growth of the Unitree Mass Storage System at the NASA Center for Computational Sciences, 3rd NASA GSFC Conference on Mass Storage Systems and Technologies, College Park, Maryland, October 1993, pp [8] Convex Computer Corporation, Unitree++ System Administration Guide, First Edition, Convex Press, Richardson, Texas, [9] Hugo R. Patterson, Garth A. Gibson, and M. Satyanarayanan, A Status Report on Research in Transparent Informed Prefetching, Operating Systems Review, vol. 27, no. 2, pp , April [10] Alan Jay Smith, Analysis of Long Term File Reference Patterns for Application to File Migration Algorithms, IEEE Transactions on Software Engineering, vol. SE-7, no. 4, pp , July [11] Alan Jay Smith, Long Term File Migration: Development and Evaluation of Algorithms, Communications of the ACM, vol. 24, no. 8, pp , August 1981.

    Article by ArticleForge

    Binding DropDownList, ListBox and CheckBoxList Control the ADO.NET way.

    This example shows how to bind DropDownList, ListBox and CheckBoxList control with data from database using the ADO.NET way.

    Note that in this demo, I’m using the Northwind database. Now let’s set up the connection string.

    STEP 1: Setting up the Connection string

    In your webnfig file set up the connection string there as shown below:

    <connectionStrings> <add name="DBConnection" connectionString="Data Source=.\SQLEXPRESS; AttachDbFilename=|DataDirectory|\Northwind.mdf; Integrated Security=True;User Instance=True" providerName="System.Data.SqlClient"> <connectionStrings>

    Note: DBConnection is the name of the Connection String that we can use as a reference in our codes later.

    In code behind, you can reference that connection string like this:

    private string GetConnectionString(){ return ConfigurationManager.ConnectionStrings["DBConnection"].ConnectionString; }

    Since we are done setting up the connection string then we can start populating the Controls, first let’s start populating the DropDownList.

    STEP 2: Populating the DropDownList

    To start, grab a DropDownList control from the visual studio ToolBox and place it the WebForm. The ASPX source should look something like this:

    <html xmlns="> <head runat="server"> <title>Binding DropDownList, ListBox and CheckBoxList<title> <head> <body> <form id="form1" runat="server"> <div> <asp:DropDownList ID="DropDownList1" runat="server"> <asp:DropDownList> <div> <form> <body> <html>

    Here’s the code block for binding the DropDownList in the code behind:

    using System; using System.Data; using System.Configuration; using System.Web; using System.Web.Security; using System.Web.UI; using System.Web.UI.WebControls; using System.Web.UI.WebControls.WebParts; using System.Web.UI.HtmlControls; using System.Data.SqlClient; using System.Collections.Specialized; using System.Text; public partial class _Default : System.Web.UI.Page { protected void Page_Load(object sender, EventArgs e) { if (!IsPostBack) { BindDropDownList(); } } private string GetConnectionString() { return ConfigurationManager.ConnectionStrings["DBConnection"].ConnectionString; } private void BindDropDownList() { DataTable dt = new DataTable(); SqlConnection connection = new SqlConnection(GetConnectionString()); try { connection.Open(); string sqlStatement = "SELECT Top(20)* FROM Customers"; SqlCommand sqlCmd = new SqlCommand(sqlStatement, connection); SqlDataAdapter sqlDa = new SqlDataAdapter(sqlCmd); sqlDa.Fill(dt); if (dt.Rows.Count > 0) { DropDownList1.DataSource =dt; DropDownList1.DataTextField = "Name"; the items to be displayed in the list items DropDownList1.DataValueField = "CustomerID"; the id of the items displayed DropDownList1.DataBind(); } } catch (System.Data.SqlClient.SqlException ex) { string msg = "Fetch Error:"; msg += ex.Message; throw new Exception(msg); } finally { connection.Close(); } } }

     

    Here’s the page output below

    STEP 3: Binding the ListBox Control

    We can bind the ListBox control the same way as what we did for binding the DropDownList by simply setting its DataTextField and DataValueField.

    Now let’s grab a ListBox control from the visual studio toolbox. The mark up should look something like this:

    <html xmlns="> <head runat="server"> <title>Binding DropDownList, ListBox and CheckBoxList<title> <head> <body> <form id="form1" runat="server"> <div> <asp:ListBox ID="ListBox1" runat="server"Height="200px" Width="100px"> <asp:ListBox> <div> <form> <body> <html>

     

    And here are the relevant codes for binding the ListBox in the code behind.

    using System; using System.Data; using System.Configuration; using System.Web; using System.Web.Security; using System.Web.UI; using System.Web.UI.WebControls; using System.Web.UI.WebControls.WebParts; using System.Web.UI.HtmlControls; using System.Data.SqlClient; using System.Collections.Specialized; using System.Text; public partial class _Default : System.Web.UI.Page { protected void Page_Load(object sender, EventArgs e) { if (!IsPostBack) { BindListBox(); } } private string GetConnectionString() { return ConfigurationManager.ConnectionStrings["DBConnection"].ConnectionString; } private void BindListBox() { DataTable dt = new DataTable(); SqlConnection connection = new SqlConnection(GetConnectionString()); try { connection.Open(); string sqlStatement = "SELECT Top(20)* FROM Customers"; SqlCommand sqlCmd = new SqlCommand(sqlStatement, connection); SqlDataAdapter sqlDa = new SqlDataAdapter(sqlCmd); sqlDa.Fill(dt); if (dt.Rows.Count > 0) { ListBox1.DataSource =dt; ListBox1.DataTextField = "Name"; the items to be displayed in the list items ListBox1.DataValueField = "CustomerID"; the id of the items displayed ListBox1.DataBind(); } } catch (System.Data.SqlClient.SqlException ex) { string msg = "Fetch Error:"; msg += ex.Message; throw new Exception(msg); } finally { connection.Close(); } } }

     

    Below is the page output:

     

    STEP 4: Binding the CheckBoxList Control

    Same procedure as what we did for DropDownList and ListBox..

    <html xmlns="> <head runat="server"> <title>Binding DropDownList, ListBox and CheckBoxList<title> <head> <body> <form id="form1" runat="server"> <div> <asp:CheckBoxList ID="CheckBoxList1" runat="server" Width="200px"> <asp:CheckBoxList> <div> <form> <body> <html>

     

    Here are relevant codes for binding the CheckBoxList in the code behind:

    using System; using System.Data; using System.Configuration; using System.Web; using System.Web.Security; using System.Web.UI; using System.Web.UI.WebControls; using System.Web.UI.WebControls.WebParts; using System.Web.UI.HtmlControls; using System.Data.SqlClient; using System.Collections.Specialized; using System.Text; public partial class _Default : System.Web.UI.Page { protected void Page_Load(object sender, EventArgs e) { if (!IsPostBack) { BindCheckBoxList(); } } private string GetConnectionString() { return ConfigurationManager.ConnectionStrings["DBConnection"].ConnectionString; } private void BindCheckBoxList() { DataTable dt = new DataTable(); SqlConnection connection = new SqlConnection(GetConnectionString()); try { connection.Open(); string sqlStatement = "SELECT Top(20)* FROM Customers"; SqlCommand sqlCmd = new SqlCommand(sqlStatement, connection); SqlDataAdapter sqlDa = new SqlDataAdapter(sqlCmd); sqlDa.Fill(dt); if (dt.Rows.Count > 0) { CheckBoxList1.RepeatColumns = 4; set the number of columns in the CheckBoxList CheckBoxList1.DataSource =dt; CheckBoxList1.DataTextField = "Name"; the items to be displayed in the list items CheckBoxList1.DataValueField = "CustomerID"; the id of the items displayed CheckBoxList1.DataBind(); } } catch (System.Data.SqlClient.SqlException ex) { string msg = "Fetch Error:"; msg += ex.Message; throw new Exception(msg); } finally { connection.Close(); } } }

    The page output will look something like below:

    That Simple! :)

    Technorati ADO.NET,ASP.NET,C#

    Article by ArticleForge

    Symantec Certifications

    Main » TERM » S »

    By Vangie Beal

    The Symantec Certification Program offers certification credentials as a means to validate an person's technical skills, knowledge and competence for many security products. Those certified have demonstrated the knowledge and skills to effectively use and manage Symantec applications, and possess high-performance technical problem solving expertise.

    Although each product varies in complexity and depth, all certification exams are created specifically for customers and cover core elements measuring technical knowledge against factors such as installation, configuration, product administration, day-to-day maintenance, and troubleshooting. Current Symantec Certification exams include the following:

  • Exam ">250-250: Administration of Storage Foundation 5.0 for UNIX
  • Exam 250-251: Administration of High Availability Solutions for UNIX using Veritas Cluster Server 5.0
  • Exam 250-270: Administration of Symantec NetBackup 7.0 for Unix
  • Exam 250-309: Administration of Symantec Enterprise Vault 9 for Exchange
  • Exam 250-311: Symantec Endpoint Protection 11.0 for Windows
  • Exam 250-314: Administration of Symantec Backup Exec 2010
  • Exam 250-351: Administration of Veritas Storage Foundation High Availability 5.0 for Windows
  • Exam 250-370: Administration of Symantec NetBackup 7.0 for Windows
  • Exam 250-400: Administration of Altiris Client Management Suite 7.0
  • Exam 250-401: Administration of Symantec Management Platform 7.0 with Notification Server
  • Exam 250-510: Administration of Symantec Data Loss Prevention 10.5
  • View details of current and legacy Symantec Certifications here.See also the list of Computer Certifications in Webopedia's Quick Reference section.

    TECH RESOURCES FROM OUR RTNERS

    Stay up to date on the latest developments in Internet terminology with a free weekly newsletter from Webopedia. Join to subscribe now.



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