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• Using VLOOKUP in Excel

  - by Mark Virtue

  VLOOKUP is one of Excel’s most useful functions, and it’s also one of the least understood.  In this article, we demystify VLOOKUP by way of a real-life example.  We’ll create a usable Invoice Template for a fictitious company. So what is VLOOKUP?  Well, of course it’s an Excel function.  This article will assume that the reader already has a passing understanding of Excel functions, and can use basic functions such as SUM, AVERAGE, and TODAY.  In its most common usage, VLOOKUP is a database function, meaning that it works with database tables – or more simply, lists of things in an Excel worksheet.  What sort of things?   Well, any sort of thing.  You may have a worksheet that contains a list of employees, or products, or customers, or CDs in your CD collection, or stars in the night sky.  It doesn’t really matter. Here’s an example of a list, or database.  In this case it’s a list of products that our fictitious company sells: Usually lists like this have some sort of unique identifier for each item in the list.  In this case, the unique identifier is in the “Item Code” column.  Note:  For the VLOOKUP function to work with a database/list, that list must have a column containing the unique identifier (or “key”, or “ID”), and that column must be the first column in the table.  Our sample database above satisfies this criterion. The hardest part of using VLOOKUP is understanding exactly what it’s for.  So let’s see if we can get that clear first: VLOOKUP retrieves information from a database/list based on a supplied instance of the unique identifier. Put another way, if you put the VLOOKUP function into a cell and pass it one of the unique identifiers from your database, it will return you one of the pieces of information associated with that unique identifier.  In the example above, you would pass VLOOKUP an item code, and it would return to you either the corresponding item’s description, its price, or its availability (its “In stock” quantity).  Which of these pieces of information will it pass you back?  Well, you get to decide this when you’re creating the formula. If all you need is one piece of information from the database, it would be a lot of trouble to go to to construct a formula with a VLOOKUP function in it.  Typically you would use this sort of functionality in a reusable spreadsheet, such as a template.  Each time someone enters a valid item code, the system would retrieve all the necessary information about the corresponding item. Let’s create an example of this:  An Invoice Template that we can reuse over and over in our fictitious company. First we start Excel… …and we create ourselves a blank invoice: This is how it’s going to work:  The person using the invoice template will fill in a series of item codes in column “A”, and the system will retrieve each item’s description and price, which will be used to calculate the line total for each item (assuming we enter a valid quantity). For the purposes of keeping this example simple, we will locate the product database on a separate sheet in the same workbook: In reality, it’s more likely that the product database would be located in a separate workbook.  It makes little difference to the VLOOKUP function, which doesn’t really care if the database is located on the same sheet, a different sheet, or a completely different workbook. In order to test the VLOOKUP formula we’re about to write, we first enter a valid item code into cell A11: Next, we move the active cell to the cell in which we want information retrieved from the database by VLOOKUP to be stored.  Interestingly, this is the step that most people get wrong.  To explain further:  We are about to create a VLOOKUP formula that will retrieve the description that corresponds to the item code in cell A11.  Where do we want this description put when we get it?  In cell B11, of course.  So that’s where we write the VLOOKUP formula – in cell B11. Select cell B11: We need to locate the list of all available functions that Excel has to offer, so that we can choose VLOOKUP and get some assistance in completing the formula.  This is found by first clicking the Formulas tab, and then clicking Insert Function:   A box appears that allows us to select any of the functions available in Excel.  To find the one we’re looking for, we could type a search term like “lookup” (because the function we’re interested in is a lookup function).  The system would return us a list of all lookup-related functions in Excel.  VLOOKUP is the second one in the list.  Select it an click OK… The Function Arguments box appears, prompting us for all the arguments (or parameters) needed in order to complete the VLOOKUP function.  You can think of this box as the function is asking us the following questions: What unique identifier are you looking up in the database? Where is the database? Which piece of information from the database, associated with the unique identifier, do you wish to have retrieved for you? The first three arguments are shown in bold, indicating that they are mandatory arguments (the VLOOKUP function is incomplete without them and will not return a valid value).  The fourth argument is not bold, meaning that it’s optional:   We will complete the arguments in order, top to bottom. The first argument we need to complete is the Lookup_value argument.  The function needs us to tell it where to find the unique identifier (the item code in this case) that it should be retuning the description of.  We must select the item code we entered earlier (in A11). Click on the selector icon to the right of the first argument: Then click once on the cell containing the item code (A11), and press Enter: The value of “A11” is inserted into the first argument. Now we need to enter a value for the Table_array argument.  In other words, we need to tell VLOOKUP where to find the database/list.  Click on the selector icon next to the second argument: Now locate the database/list and select the entire list – not including the header line.  The database is located on a separate worksheet, so we first click on that worksheet tab: Next we select the entire database, not including the header line: …and press Enter.  The range of cells that represents the database (in this case “’Product Database’!A2:D7”) is entered automatically for us into the second argument. Now we need to enter the third argument, Col_index_num.  We use this argument to specify to VLOOKUP which piece of information from the database, associate with our item code in A11, we wish to have returned to us.  In this particular example, we wish to have the item’s description returned to us.  If you look on the database worksheet, you’ll notice that the “Description” column is the second column in the database.  This means that we must enter a value of “2” into the Col_index_num box: It is important to note that that we are not entering a “2” here because the “Description” column is in the B column on that worksheet.  If the database happened to start in column K of the worksheet, we would still enter a “2” in this field. Finally, we need to decide whether to enter a value into the final VLOOKUP argument, Range_lookup.  This argument requires either a true or false value, or it should be left blank.  When using VLOOKUP with databases (as is true 90% of the time), then the way to decide what to put in this argument can be thought of as follows: If the first column of the database (the column that contains the unique identifiers) is sorted alphabetically/numerically in ascending order, then it’s possible to enter a value of true into this argument, or leave it blank. If the first column of the database is not sorted, or it’s sorted in descending order, then you must enter a value of false into this argument As the first column of our database is not sorted, we enter false into this argument: That’s it!  We’ve entered all the information required for VLOOKUP to return the value we need.  Click the OK button and notice that the description corresponding to item code “R99245” has been correctly entered into cell B11: The formula that was created for us looks like this: If we enter a different item code into cell A11, we will begin to see the power of the VLOOKUP function:  The description cell changes to match the new item code: We can perform a similar set of steps to get the item’s price returned into cell E11.  Note that the new formula must be created in cell E11.  The result will look like this: …and the formula will look like this: Note that the only difference between the two formulae is the third argument (Col_index_num) has changed from a “2” to a “3” (because we want data retrieved from the 3rd column in the database). If we decided to buy 2 of these items, we would enter a “2” into cell D11.  We would then enter a simple formula into cell F11 to get the line total: =D11*E11 …which looks like this… Completing the Invoice Template We’ve learned a lot about VLOOKUP so far.  In fact, we’ve learned all we’re going to learn in this article.  It’s important to note that VLOOKUP can be used in other circumstances besides databases.  This is less common, and may be covered in future How-To Geek articles. Our invoice template is not yet complete.  In order to complete it, we would do the following: We would remove the sample item code from cell A11 and the “2” from cell D11.  This will cause our newly created VLOOKUP formulae to display error messages: We can remedy this by judicious use of Excel’s IF() and ISBLANK() functions.  We change our formula from this…       =VLOOKUP(A11,’Product Database’!A2:D7,2,FALSE) …to this…       =IF(ISBLANK(A11),”",VLOOKUP(A11,’Product Database’!A2:D7,2,FALSE)) We would copy the formulas in cells B11, E11 and F11 down to the remainder of the item rows of the invoice.  Note that if we do this, the resulting formulas will no longer correctly refer to the database table.  We could fix this by changing the cell references for the database to absolute cell references.  Alternatively – and even better – we could create a range name for the entire product database (such as “Products”), and use this range name instead of the cell references.  The formula would change from this…       =IF(ISBLANK(A11),”",VLOOKUP(A11,’Product Database’!A2:D7,2,FALSE)) …to this…       =IF(ISBLANK(A11),”",VLOOKUP(A11,Products,2,FALSE)) …and then copy the formulas down to the rest of the invoice item rows. We would probably “lock” the cells that contain our formulae (or rather unlock the other cells), and then protect the worksheet, in order to ensure that our carefully constructed formulae are not accidentally overwritten when someone comes to fill in the invoice. We would save the file as a template, so that it could be reused by everyone in our company If we were feeling really clever, we would create a database of all our customers in another worksheet, and then use the customer ID entered in cell F5 to automatically fill in the customer’s name and address in cells B6, B7 and B8. If you would like to practice with VLOOKUP, or simply see our resulting Invoice Template, it can be downloaded from here. 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• Using Oracle Proxy Authentication with JPA (eclipselink-Style)

  - by olaf.heimburger

  Security is a very intriguing topic. You will find it everywhere and you need to implement it everywhere. Yes, you need. Unfortunately, one can easily forget it while implementing the last mile. The Last Mile In a multi-tier application it is a common practice to use connection pools between the business layer and the database layer. Connection pools are quite useful to speed database connection creation and to split the load. Another very common practice is to use a specific, often called technical, user to connect to the database. This user has authentication and authorization rules that apply to all application users. Imagine you've put every effort to define roles for different types of users that use your application. These roles are necessary to differentiate between normal users, premium users, and administrators (I bet you will find or already have more roles in your application). While these user roles are pretty well used within your application, once the flow of execution enters the database everything is gone. Each and every user just has one role and is the same database user. Issues? What Issues? As long as things go well, this is not a real issue. However, things do not go well all the time. Once your application becomes famous performance decreases in certain situations or, more importantly, current and upcoming regulations and laws require that your application must be able to apply different security measures on a per user role basis at every stage of your application. If you only have a bunch of users with the same name and role you are not able to find the application usage profile that causes the performance issue, or which user has accessed data that he/she is not allowed to. Another thread to your role concept is that databases tend to be used by different applications and tools. These tools can be developer tools like SQL*Plus, SQL Developer, etc. or end user applications like BI Publisher, Oracle Forms and so on. These tools have no idea of your applications role concept and access the database the way they think is appropriate. A big oversight for your perfect role model and a big nightmare for your Chief Security Officer. Speaking of the CSO, brings up another issue: Password management. Once your technical user account is compromised, every user is able to do things that he/she is not expected to do from the design of your application. Counter Measures In the Oracle world a common counter measure is to use Virtual Private Database (VPD). This restricts the values a database user can see to the allowed minimum. However, it doesn't help in regard of a connection pool user, because this one is still not the real user. Oracle Proxy Authentication Another feature of the Oracle database is Proxy Authentication. First introduced with version 9i it is a quite useful feature for nearly every situation. The main idea behind Proxy Authentication is, to create a crippled database user who has only connect rights. Even if this user is compromised the risks are well understood and fairly limited. This user can be used in every situation in which you need to connect to the database, no matter which tool or application (see above) you use.The proxy user is perfect for multi-tier connection pools. CREATE USER app_user IDENTIFIED BY abcd1234; GRANT CREATE SESSION TO app_user; But what if you need to access real data? Well, this is the primary use case, isn't it? Now is the time to bring the application's role concept into play. You define database roles that define the grants for your identified user groups. Once you have these groups you grant access through the proxy user with the application role to the specific user. CREATE ROLE app_role_a; GRANT app_role_a TO scott; ALTER USER scott GRANT CONNECT THROUGH app_user WITH ROLE app_role_a; Now, hr has permission to connect to the database through the proxy user. Through the role you can restrict the hr's rights the are needed for the application only. If hr connects to the database directly all assigned role and permissions apply. Testing the Setup To test the setup you can use SQL*Plus and connect to your database: $ sqlplus app_user[hr]/abcd1234 Java Persistence API The Java Persistence API (JPA) is a fairly easy means to build applications that retrieve data from the database and put it into Java objects. You use plain old Java objects (POJOs) and mixin some Java annotations that define how the attributes of the object are used for storing data from the database into the Java object. Here is a sample for objects from the HR sample schema EMPLOYEES table. When using Java annotations you only specify what can not be deduced from the code. If your Java class name is Employee but the table name is EMPLOYEES, you need to specify the table name, otherwise it will fail. package demo.proxy.ejb; import java.io.Serializable; import java.sql.Timestamp; import java.util.List; import javax.persistence.Column; import javax.persistence.Entity; import javax.persistence.Id; import javax.persistence.JoinColumn; import javax.persistence.ManyToOne; import javax.persistence.NamedQueries; import javax.persistence.NamedQuery; import javax.persistence.OneToMany; import javax.persistence.Table; @Entity @NamedQueries({ @NamedQuery(name = "Employee.findAll", query = "select o from Employee o") }) @Table(name = "EMPLOYEES") public class Employee implements Serializable { @Column(name="COMMISSION_PCT") private Double commissionPct; @Column(name="DEPARTMENT_ID") private Long departmentId; @Column(nullable = false, unique = true, length = 25) private String email; @Id @Column(name="EMPLOYEE_ID", nullable = false) private Long employeeId; @Column(name="FIRST_NAME", length = 20) private String firstName; @Column(name="HIRE_DATE", nullable = false) private Timestamp hireDate; @Column(name="JOB_ID", nullable = false, length = 10) private String jobId; @Column(name="LAST_NAME", nullable = false, length = 25) private String lastName; @Column(name="PHONE_NUMBER", length = 20) private String phoneNumber; private Double salary; @ManyToOne @JoinColumn(name = "MANAGER_ID") private Employee employee; @OneToMany(mappedBy = "employee") private List employeeList; public Employee() { } public Employee(Double commissionPct, Long departmentId, String email, Long employeeId, String firstName, Timestamp hireDate, String jobId, String lastName, Employee employee, String phoneNumber, Double salary) { this.commissionPct = commissionPct; this.departmentId = departmentId; this.email = email; this.employeeId = employeeId; this.firstName = firstName; this.hireDate = hireDate; this.jobId = jobId; this.lastName = lastName; this.employee = employee; this.phoneNumber = phoneNumber; this.salary = salary; } public Double getCommissionPct() { return commissionPct; } public void setCommissionPct(Double commissionPct) { this.commissionPct = commissionPct; } public Long getDepartmentId() { return departmentId; } public void setDepartmentId(Long departmentId) { this.departmentId = departmentId; } public String getEmail() { return email; } public void setEmail(String email) { this.email = email; } public Long getEmployeeId() { return employeeId; } public void setEmployeeId(Long employeeId) { this.employeeId = employeeId; } public String getFirstName() { return firstName; } public void setFirstName(String firstName) { this.firstName = firstName; } public Timestamp getHireDate() { return hireDate; } public void setHireDate(Timestamp hireDate) { this.hireDate = hireDate; } public String getJobId() { return jobId; } public void setJobId(String jobId) { this.jobId = jobId; } public String getLastName() { return lastName; } public void setLastName(String lastName) { this.lastName = lastName; } public String getPhoneNumber() { return phoneNumber; } public void setPhoneNumber(String phoneNumber) { this.phoneNumber = phoneNumber; } public Double getSalary() { return salary; } public void setSalary(Double salary) { this.salary = salary; } public Employee getEmployee() { return employee; } public void setEmployee(Employee employee) { this.employee = employee; } public List getEmployeeList() { return employeeList; } public void setEmployeeList(List employeeList) { this.employeeList = employeeList; } public Employee addEmployee(Employee employee) { getEmployeeList().add(employee); employee.setEmployee(this); return employee; } public Employee removeEmployee(Employee employee) { getEmployeeList().remove(employee); employee.setEmployee(null); return employee; } } JPA could be used in standalone applications and Java EE containers. In both worlds you normally create a Facade to retrieve or store the values of the Entities to or from the database. The Facade does this via an EntityManager which will be injected by the Java EE container. Here is sample Facade Session Bean for a Java EE container. package demo.proxy.ejb; import java.util.HashMap; import java.util.List; import javax.ejb.Local; import javax.ejb.Remote; import javax.ejb.Stateless; import javax.persistence.EntityManager; import javax.persistence.PersistenceContext; import javax.persistence.Query; import javax.interceptor.AroundInvoke; import javax.interceptor.InvocationContext; import oracle.jdbc.driver.OracleConnection; import org.eclipse.persistence.config.EntityManagerProperties; import org.eclipse.persistence.internal.jpa.EntityManagerImpl; @Stateless(name = "DataFacade", mappedName = "ProxyUser-TestEJB-DataFacade") @Remote @Local public class DataFacadeBean implements DataFacade, DataFacadeLocal { @PersistenceContext(unitName = "TestEJB") private EntityManager em; private String username; public Object queryByRange(String jpqlStmt, int firstResult, int maxResults) { // setSessionUser(); Query query = em.createQuery(jpqlStmt); if (firstResult 0) { query = query.setFirstResult(firstResult); } if (maxResults 0) { query = query.setMaxResults(maxResults); } return query.getResultList(); } public Employee persistEmployee(Employee employee) { // setSessionUser(); em.persist(employee); return employee; } public Employee mergeEmployee(Employee employee) { // setSessionUser(); return em.merge(employee); } public void removeEmployee(Employee employee) { // setSessionUser(); employee = em.find(Employee.class, employee.getEmployeeId()); em.remove(employee); } /** select o from Employee o */ public List getEmployeeFindAll() { Query q = em.createNamedQuery("Employee.findAll"); return q.getResultList(); } Putting Both Together To use Proxy Authentication with JPA and within a Java EE container you have to take care of the additional requirements: Use an OCI JDBC driver Provide the user name that connects through the proxy user Use an OCI JDBC driver To use the OCI JDBC driver you need to set up your JDBC data source file to use the correct JDBC URL. hr jdbc:oracle:oci8:@(DESCRIPTION=(ADDRESS=(PROTOCOL=TCP)(HOST=localhost)(PORT=1521))(CONNECT_DATA=(SID=XE))) oracle.jdbc.OracleDriver user app_user 62C32F70E98297522AD97E15439FAC0E SQL SELECT 1 FROM DUAL jdbc/hrDS Application Additionally you need to make sure that the version of the shared libraries of the OCI driver match the version of the JDBC driver in your Java EE container or Java application and are within your PATH (on Windows) or LD_LIBRARY_PATH (on most Unix-based systems). Installing the Oracle Database Instance Client software works perfectly. Provide the user name that connects through the proxy user This part needs some modification of your application software and session facade. Session Facade Changes In the Session Facade we must ensure that every call that goes through the EntityManager must be prepared correctly and uniquely assigned to this session. The second is really important, as the EntityManager works with a connection pool and can not guarantee that we set the proxy user on the connection that will be used for the database activities. To avoid changing every method call of the Session Facade we provide a method to set the username of the user that connects through the proxy user. This method needs to be called by the Facade client bfore doing anything else. public void setUsername(String name) { username = name; } Next we provide a means to instruct the TopLink EntityManager Delegate to use Oracle Proxy Authentication. (I love small helper methods to hide the nitty-gritty details and avoid repeating myself.) private void setSessionUser() { setSessionUser(username); } private void setSessionUser(String user) { if (user != null && !user.isEmpty()) { EntityManagerImpl emDelegate = ((EntityManagerImpl)em.getDelegate()); emDelegate.setProperty(EntityManagerProperties.ORACLE_PROXY_TYPE, OracleConnection.PROXYTYPE_USER_NAME); emDelegate.setProperty(OracleConnection.PROXY_USER_NAME, user); emDelegate.setProperty(EntityManagerProperties.EXCLUSIVE_CONNECTION_MODE, "Always"); } } The final step is use the EJB 3.0 AroundInvoke interceptor. This interceptor will be called around every method invocation. We therefore check whether the Facade methods will be called or not. If so, we set the user for proxy authentication and the normal method flow continues. @AroundInvoke public Object proxyInterceptor(InvocationContext invocationCtx) throws Exception { if (invocationCtx.getTarget() instanceof DataFacadeBean) { setSessionUser(); } return invocationCtx.proceed(); } Benefits Using Oracle Proxy Authentification has a number of additional benefits appart from implementing the role model of your application: Fine grained access control for temporary users of the account, without compromising the original password. Enabling database auditing and logging. Better identification of performance bottlenecks. References Effective Oracle Database 10g Security by Design, David Knox TopLink Developer's Guide, Chapter 98

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• The Benefits of Smart Grid Business Software

  - by Sylvie MacKenzie, PMP

  Smart Grid Background What Are Smart Grids?Smart Grids use computer hardware and software, sensors, controls, and telecommunications equipment and services to: Link customers to information that helps them manage consumption and use electricity wisely. Enable customers to respond to utility notices in ways that help minimize the duration of overloads, bottlenecks, and outages. Provide utilities with information that helps them improve performance and control costs. What Is Driving Smart Grid Development? Environmental ImpactSmart Grid development is picking up speed because of the widespread interest in reducing the negative impact that energy use has on the environment. Smart Grids use technology to drive efficiencies in transmission, distribution, and consumption. As a result, utilities can serve customers’ power needs with fewer generating plants, fewer transmission and distribution assets,and lower overall generation. With the possible exception of wind farm sprawl, landscape preservation is one obvious benefit. And because most generation today results in greenhouse gas emissions, Smart Grids reduce air pollution and the potential for global climate change.Smart Grids also more easily accommodate the technical difficulties of integrating intermittent renewable resources like wind and solar into the grid, providing further greenhouse gas reductions. CostsThe ability to defer the cost of plant and grid expansion is a major benefit to both utilities and customers. Utilities do not need to use as many internal resources for traditional infrastructure project planning and management. Large T&D infrastructure expansion costs are not passed on to customers.Smart Grids will not eliminate capital expansion, of course. Transmission corridors to connect renewable generation with customers will require major near-term expenditures. Additionally, in the future, electricity to satisfy the needs of population growth and additional applications will exceed the capacity reductions available through the Smart Grid. At that point, expansion will resume—but with greater overall T&D efficiency based on demand response, load control, and many other Smart Grid technologies and business processes. Energy efficiency is a second area of Smart Grid cost saving of particular relevance to customers. The timely and detailed information Smart Grids provide encourages customers to limit waste, adopt energy-efficient building codes and standards, and invest in energy efficient appliances. Efficiency may or may not lower customer bills because customer efficiency savings may be offset by higher costs in generation fuels or carbon taxes. It is clear, however, that bills will be lower with efficiency than without it. Utility Operations Smart Grids can serve as the central focus of utility initiatives to improve business processes. Many utilities have long “wish lists” of projects and applications they would like to fund in order to improve customer service or ease staff’s burden of repetitious work, but they have difficulty cost-justifying the changes, especially in the short term. Adding Smart Grid benefits to the cost/benefit analysis frequently tips the scales in favor of the change and can also significantly reduce payback periods.Mobile workforce applications and asset management applications work together to deploy assets and then to maintain, repair, and replace them. Many additional benefits result—for instance, increased productivity and fuel savings from better routing. Similarly, customer portals that provide customers with near-real-time information can also encourage online payments, thus lowering billing costs. Utilities can and should include these cost and service improvements in the list of Smart Grid benefits. What Is Smart Grid Business Software? Smart Grid business software gathers data from a Smart Grid and uses it improve a utility’s business processes. Smart Grid business software also helps utilities provide relevant information to customers who can then use it to reduce their own consumption and improve their environmental profiles. Smart Grid Business Software Minimizes the Impact of Peak Demand Utilities must size their assets to accommodate their highest peak demand. The higher the peak rises above base demand: The more assets a utility must build that are used only for brief periods—an inefficient use of capital. The higher the utility’s risk profile rises given the uncertainties surrounding the time needed for permitting, building, and recouping costs. The higher the costs for utilities to purchase supply, because generators can charge more for contracts and spot supply during high-demand periods. Smart Grids enable a variety of programs that reduce peak demand, including: Time-of-use pricing and critical peak pricing—programs that charge customers more when they consume electricity during peak periods. Pilot projects indicate that these programs are successful in flattening peaks, thus ensuring better use of existing T&D and generation assets. Direct load control, which lets utilities reduce or eliminate electricity flow to customer equipment (such as air conditioners). Contracts govern the terms and conditions of these turn-offs. Indirect load control, which signals customers to reduce the use of on-premises equipment for contractually agreed-on time periods. Smart Grid business software enables utilities to impose penalties on customers who do not comply with their contracts. Smart Grids also help utilities manage peaks with existing assets by enabling: Real-time asset monitoring and control. In this application, advanced sensors safely enable dynamic capacity load limits, ensuring that all grid assets can be used to their maximum capacity during peak demand periods. Real-time asset monitoring and control applications also detect the location of excessive losses and pinpoint need for mitigation and asset replacements. As a result, utilities reduce outage risk and guard against excess capacity or “over-build”. Better peak demand analysis. As a result: Distribution planners can better size equipment (e.g. transformers) to avoid over-building. Operations engineers can identify and resolve bottlenecks and other inefficiencies that may cause or exacerbate peaks. As above, the result is a reduction in the tendency to over-build. Supply managers can more closely match procurement with delivery. As a result, they can fine-tune supply portfolios, reducing the tendency to over-contract for peak supply and reducing the need to resort to spot market purchases during high peaks. Smart Grids can help lower the cost of remaining peaks by: Standardizing interconnections for new distributed resources (such as electricity storage devices). Placing the interconnections where needed to support anticipated grid congestion. Smart Grid Business Software Lowers the Cost of Field Services By processing Smart Grid data through their business software, utilities can reduce such field costs as: Vegetation management. Smart Grids can pinpoint momentary interruptions and tree-caused outages. Spatial mash-up tools leverage GIS models of tree growth for targeted vegetation management. This reduces the cost of unnecessary tree trimming. Service vehicle fuel. Many utility service calls are “false alarms.” Checking meter status before dispatching crews prevents many unnecessary “truck rolls.” Similarly, crews use far less fuel when Smart Grid sensors can pinpoint a problem and mobile workforce applications can then route them directly to it. Smart Grid Business Software Ensures Regulatory Compliance Smart Grids can ensure compliance with private contracts and with regional, national, or international requirements by: Monitoring fulfillment of contract terms. Utilities can use one-hour interval meters to ensure that interruptible (“non-core”) customers actually reduce or eliminate deliveries as required. They can use the information to levy fines against contract violators. Monitoring regulations imposed on customers, such as maximum use during specific time periods. Using accurate time-stamped event history derived from intelligent devices distributed throughout the smart grid to monitor and report reliability statistics and risk compliance. Automating business processes and activities that ensure compliance with security and reliability measures (e.g. NERC-CIP 2-9). Grid Business Software Strengthens Utilities’ Connection to Customers While Reducing Customer Service Costs During outages, Smart Grid business software can: Identify outages more quickly. Software uses sensors to pinpoint outages and nested outage locations. They also permit utilities to ensure outage resolution at every meter location. Size outages more accurately, permitting utilities to dispatch crews that have the skills needed, in appropriate numbers. Provide updates on outage location and expected duration. This information helps call centers inform customers about the timing of service restoration. Smart Grids also facilitates display of outage maps for customer and public-service use. Smart Grids can significantly reduce the cost to: Connect and disconnect customers. Meters capable of remote disconnect can virtually eliminate the costs of field crews and vehicles previously required to change service from the old to the new residents of a metered property or disconnect customers for nonpayment. Resolve reports of voltage fluctuation. Smart Grids gather and report voltage and power quality data from meters and grid sensors, enabling utilities to pinpoint reported problems or resolve them before customers complain. Detect and resolve non-technical losses (e.g. theft). Smart Grids can identify illegal attempts to reconnect meters or to use electricity in supposedly vacant premises. They can also detect theft by comparing flows through delivery assets with billed consumption. Smart Grids also facilitate outreach to customers. By monitoring and analyzing consumption over time, utilities can: Identify customers with unusually high usage and contact them before they receive a bill. They can also suggest conservation techniques that might help to limit consumption. This can head off “high bill” complaints to the contact center. Note that such “high usage” or “additional charges apply because you are out of range” notices—frequently via text messaging—are already common among mobile phone providers. Help customers identify appropriate bill payment alternatives (budget billing, prepayment, etc.). Help customers find and reduce causes of over-consumption. There’s no waiting for bills in the mail before they even understand there is a problem. Utilities benefit not just through improved customer relations but also through limiting the size of bills from customers who might struggle to pay them. Where permitted, Smart Grids can open the doors to such new utility service offerings as: Monitoring properties. Landlords reduce costs of vacant properties when utilities notify them of unexpected energy or water consumption. Utilities can perform similar services for owners of vacation properties or the adult children of aging parents. Monitoring equipment. Power-use patterns can reveal a need for equipment maintenance. Smart Grids permit utilities to alert owners or managers to a need for maintenance or replacement. Facilitating home and small-business networks. Smart Grids can provide a gateway to equipment networks that automate control or let owners access equipment remotely. They also facilitate net metering, offering some utilities a path toward involvement in small-scale solar or wind generation. Prepayment plans that do not need special meters. Smart Grid Business Software Helps Customers Control Energy Costs There is no end to the ways Smart Grids help both small and large customers control energy costs. For instance: Multi-premises customers appreciate having all meters read on the same day so that they can more easily compare consumption at various sites. Customers in competitive regions can match their consumption profile (detailed via Smart Grid data) with specific offerings from competitive suppliers. Customers seeing inexplicable consumption patterns and power quality problems may investigate further. The result can be discovery of electrical problems that can be resolved through rewiring or maintenance—before more serious fires or accidents happen. Smart Grid Business Software Facilitates Use of Renewables Generation from wind and solar resources is a popular alternative to fossil fuel generation, which emits greenhouse gases. Wind and solar generation may also increase energy security in regions that currently import fossil fuel for use in generation. Utilities face many technical issues as they attempt to integrate intermittent resource generation into traditional grids, which traditionally handle only fully dispatchable generation. Smart Grid business software helps solves many of these issues by: Detecting sudden drops in production from renewables-generated electricity (wind and solar) and automatically triggering electricity storage and smart appliance response to compensate as needed. Supporting industry-standard distributed generation interconnection processes to reduce interconnection costs and avoid adding renewable supplies to locations already subject to grid congestion. Facilitating modeling and monitoring of locally generated supply from renewables and thus helping to maximize their use. Increasing the efficiency of “net metering” (through which utilities can use electricity generated by customers) by: Providing data for analysis. Integrating the production and consumption aspects of customer accounts. During non-peak periods, such techniques enable utilities to increase the percent of renewable generation in their supply mix. During peak periods, Smart Grid business software controls circuit reconfiguration to maximize available capacity. Conclusion Utility missions are changing. Yesterday, they focused on delivery of reasonably priced energy and water. Tomorrow, their missions will expand to encompass sustainable use and environmental improvement.Smart Grids are key to helping utilities achieve this expanded mission. But they come at a relatively high price. Utilities will need to invest heavily in new hardware, software, business process development, and staff training. Customer investments in home area networks and smart appliances will be large. Learning to change the energy and water consumption habits of a lifetime could ultimately prove even more formidable tasks.Smart Grid business software can ease the cost and difficulties inherent in a needed transition to a more flexible, reliable, responsive electricity grid. Justifying its implementation, however, requires a full understanding of the benefits it brings—benefits that can ultimately help customers, utilities, communities, and the world address global issues like energy security and climate change while minimizing costs and maximizing customer convenience. This white paper is available for download here. For further information about Oracle's Primavera Solutions for Utilities, please read our Utilities e-book.

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• What's up with OCFS2?

  - by wcoekaer

  On Linux there are many filesystem choices and even from Oracle we provide a number of filesystems, all with their own advantages and use cases. Customers often confuse ACFS with OCFS or OCFS2 which then causes assumptions to be made such as one replacing the other etc... I thought it would be good to write up a summary of how OCFS2 got to where it is, what we're up to still, how it is different from other options and how this really is a cool native Linux cluster filesystem that we worked on for many years and is still widely used. Work on a cluster filesystem at Oracle started many years ago, in the early 2000's when the Oracle Database Cluster development team wrote a cluster filesystem for Windows that was primarily focused on providing an alternative to raw disk devices and help customers with the deployment of Oracle Real Application Cluster (RAC). Oracle RAC is a cluster technology that lets us make a cluster of Oracle Database servers look like one big database. The RDBMS runs on many nodes and they all work on the same data. It's a Shared Disk database design. There are many advantages doing this but I will not go into detail as that is not the purpose of my write up. Suffice it to say that Oracle RAC expects all the database data to be visible in a consistent, coherent way, across all the nodes in the cluster. To do that, there were/are a few options : 1) use raw disk devices that are shared, through SCSI, FC, or iSCSI 2) use a network filesystem (NFS) 3) use a cluster filesystem(CFS) which basically gives you a filesystem that's coherent across all nodes using shared disks. It is sort of (but not quite) combining option 1 and 2 except that you don't do network access to the files, the files are effectively locally visible as if it was a local filesystem. So OCFS (Oracle Cluster FileSystem) on Windows was born. Since Linux was becoming a very important and popular platform, we decided that we would also make this available on Linux and thus the porting of OCFS/Windows started. The first version of OCFS was really primarily focused on replacing the use of Raw devices with a simple filesystem that lets you create files and provide direct IO to these files to get basically native raw disk performance. The filesystem was not designed to be fully POSIX compliant and it did not have any where near good/decent performance for regular file create/delete/access operations. Cache coherency was easy since it was basically always direct IO down to the disk device and this ensured that any time one issues a write() command it would go directly down to the disk, and not return until the write() was completed. Same for read() any sort of read from a datafile would be a read() operation that went all the way to disk and return. We did not cache any data when it came down to Oracle data files. So while OCFS worked well for that, since it did not have much of a normal filesystem feel, it was not something that could be submitted to the kernel mail list for inclusion into Linux as another native linux filesystem (setting aside the Windows porting code ...) it did its job well, it was very easy to configure, node membership was simple, locking was disk based (so very slow but it existed), you could create regular files and do regular filesystem operations to a certain extend but anything that was not database data file related was just not very useful in general. Logfiles ok, standard filesystem use, not so much. Up to this point, all the work was done, at Oracle, by Oracle developers. Once OCFS (1) was out for a while and there was a lot of use in the database RAC world, many customers wanted to do more and were asking for features that you'd expect in a normal native filesystem, a real "general purposes cluster filesystem". So the team sat down and basically started from scratch to implement what's now known as OCFS2 (Oracle Cluster FileSystem release 2). Some basic criteria were : Design it with a real Distributed Lock Manager and use the network for lock negotiation instead of the disk Make it a Linux native filesystem instead of a native shim layer and a portable core Support standard Posix compliancy and be fully cache coherent with all operations Support all the filesystem features Linux offers (ACL, extended Attributes, quotas, sparse files,...) Be modern, support large files, 32/64bit, journaling, data ordered journaling, endian neutral, we can mount on both endian /cross architecture,.. Needless to say, this was a huge development effort that took many years to complete. A few big milestones happened along the way... OCFS2 was development in the open, we did not have a private tree that we worked on without external code review from the Linux Filesystem maintainers, great folks like Christopher Hellwig reviewed the code regularly to make sure we were not doing anything out of line, we submitted the code for review on lkml a number of times to see if we were getting close for it to be included into the mainline kernel. Using this development model is standard practice for anyone that wants to write code that goes into the kernel and having any chance of doing so without a complete rewrite or.. shall I say flamefest when submitted. It saved us a tremendous amount of time by not having to re-fit code for it to be in a Linus acceptable state. Some other filesystems that were trying to get into the kernel that didn't follow an open development model had a lot harder time and a lot harsher criticism. March 2006, when Linus released 2.6.16, OCFS2 officially became part of the mainline kernel, it was accepted a little earlier in the release candidates but in 2.6.16. OCFS2 became officially part of the mainline Linux kernel tree as one of the many filesystems. It was the first cluster filesystem to make it into the kernel tree. Our hope was that it would then end up getting picked up by the distribution vendors to make it easy for everyone to have access to a CFS. Today the source code for OCFS2 is approximately 85000 lines of code. We made OCFS2 production with full support for customers that ran Oracle database on Linux, no extra or separate support contract needed. OCFS2 1.0.0 started being built for RHEL4 for x86, x86-64, ppc, s390x and ia64. For RHEL5 starting with OCFS2 1.2. SuSE was very interested in high availability and clustering and decided to build and include OCFS2 with SLES9 for their customers and was, next to Oracle, the main contributor to the filesystem for both new features and bug fixes. Source code was always available even prior to inclusion into mainline and as of 2.6.16, source code was just part of a Linux kernel download from kernel.org, which it still is, today. So the latest OCFS2 code is always the upstream mainline Linux kernel. OCFS2 is the cluster filesystem used in Oracle VM 2 and Oracle VM 3 as the virtual disk repository filesystem. Since the filesystem is in the Linux kernel it's released under the GPL v2 The release model has always been that new feature development happened in the mainline kernel and we then built consistent, well tested, snapshots that had versions, 1.2, 1.4, 1.6, 1.8. But these releases were effectively just snapshots in time that were tested for stability and release quality. OCFS2 is very easy to use, there's a simple text file that contains the node information (hostname, node number, cluster name) and a file that contains the cluster heartbeat timeouts. It is very small, and very efficient. As Sunil Mushran wrote in the manual : OCFS2 is an efficient, easily configured, quickly installed, fully integrated and compatible, feature-rich, architecture and endian neutral, cache coherent, ordered data journaling, POSIX-compliant, shared disk cluster file system. Here is a list of some of the important features that are included : Variable Block and Cluster sizes Supports block sizes ranging from 512 bytes to 4 KB and cluster sizes ranging from 4 KB to 1 MB (increments in power of 2). Extent-based Allocations Tracks the allocated space in ranges of clusters making it especially efficient for storing very large files. Optimized Allocations Supports sparse files, inline-data, unwritten extents, hole punching and allocation reservation for higher performance and efficient storage. File Cloning/snapshots REFLINK is a feature which introduces copy-on-write clones of files in a cluster coherent way. Indexed Directories Allows efficient access to millions of objects in a directory. Metadata Checksums Detects silent corruption in inodes and directories. Extended Attributes Supports attaching an unlimited number of name:value pairs to the file system objects like regular files, directories, symbolic links, etc. Advanced Security Supports POSIX ACLs and SELinux in addition to the traditional file access permission model. Quotas Supports user and group quotas. Journaling Supports both ordered and writeback data journaling modes to provide file system consistency in the event of power failure or system crash. Endian and Architecture neutral Supports a cluster of nodes with mixed architectures. Allows concurrent mounts on nodes running 32-bit and 64-bit, little-endian (x86, x86_64, ia64) and big-endian (ppc64) architectures. In-built Cluster-stack with DLM Includes an easy to configure, in-kernel cluster-stack with a distributed lock manager. Buffered, Direct, Asynchronous, Splice and Memory Mapped I/Os Supports all modes of I/Os for maximum flexibility and performance. Comprehensive Tools Support Provides a familiar EXT3-style tool-set that uses similar parameters for ease-of-use. The filesystem was distributed for Linux distributions in separate RPM form and this had to be built for every single kernel errata release or every updated kernel provided by the vendor. We provided builds from Oracle for Oracle Linux and all kernels released by Oracle and for Red Hat Enterprise Linux. SuSE provided the modules directly for every kernel they shipped. With the introduction of the Unbreakable Enterprise Kernel for Oracle Linux and our interest in reducing the overhead of building filesystem modules for every minor release, we decide to make OCFS2 available as part of UEK. There was no more need for separate kernel modules, everything was built-in and a kernel upgrade automatically updated the filesystem, as it should. UEK allowed us to not having to backport new upstream filesystem code into an older kernel version, backporting features into older versions introduces risk and requires extra testing because the code is basically partially rewritten. The UEK model works really well for continuing to provide OCFS2 without that extra overhead. Because the RHEL kernel did not contain OCFS2 as a kernel module (it is in the source tree but it is not built by the vendor in kernel module form) we stopped adding the extra packages to Oracle Linux and its RHEL compatible kernel and for RHEL. Oracle Linux customers/users obviously get OCFS2 included as part of the Unbreakable Enterprise Kernel, SuSE customers get it by SuSE distributed with SLES and Red Hat can decide to distribute OCFS2 to their customers if they chose to as it's just a matter of compiling the module and making it available. OCFS2 today, in the mainline kernel is pretty much feature complete in terms of integration with every filesystem feature Linux offers and it is still actively maintained with Joel Becker being the primary maintainer. Since we use OCFS2 as part of Oracle VM, we continue to look at interesting new functionality to add, REFLINK was a good example, and as such we continue to enhance the filesystem where it makes sense. Bugfixes and any sort of code that goes into the mainline Linux kernel that affects filesystems, automatically also modifies OCFS2 so it's in kernel, actively maintained but not a lot of new development happening at this time. We continue to fully support OCFS2 as part of Oracle Linux and the Unbreakable Enterprise Kernel and other vendors make their own decisions on support as it's really a Linux cluster filesystem now more than something that we provide to customers. It really just is part of Linux like EXT3 or BTRFS etc, the OS distribution vendors decide. Do not confuse OCFS2 with ACFS (ASM cluster Filesystem) also known as Oracle Cloud Filesystem. ACFS is a filesystem that's provided by Oracle on various OS platforms and really integrates into Oracle ASM (Automatic Storage Management). It's a very powerful Cluster Filesystem but it's not distributed as part of the Operating System, it's distributed with the Oracle Database product and installs with and lives inside Oracle ASM. ACFS obviously is fully supported on Linux (Oracle Linux, Red Hat Enterprise Linux) but OCFS2 independently as a native Linux filesystem is also, and continues to also be supported. ACFS is very much tied into the Oracle RDBMS, OCFS2 is just a standard native Linux filesystem with no ties into Oracle products. Customers running the Oracle database and ASM really should consider using ACFS as it also provides storage/clustered volume management. Customers wanting to use a simple, easy to use generic Linux cluster filesystem should consider using OCFS2. To learn more about OCFS2 in detail, you can find good documentation on http://oss.oracle.com/projects/ocfs2 in the Documentation area, or get the latest mainline kernel from http://kernel.org and read the source. One final, unrelated note - since I am not always able to publicly answer or respond to comments, I do not want to selectively publish comments from readers. Sometimes I forget to publish comments, sometime I publish them and sometimes I would publish them but if for some reason I cannot publicly comment on them, it becomes a very one-sided stream. So for now I am going to not publish comments from anyone, to be fair to all sides. You are always welcome to email me and I will do my best to respond to technical questions, questions about strategy or direction are sometimes not possible to answer for obvious reasons.

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• Windows Azure Service Bus Splitter and Aggregator

  - by Alan Smith

  This article will cover basic implementations of the Splitter and Aggregator patterns using the Windows Azure Service Bus. The content will be included in the next release of the “Windows Azure Service Bus Developer Guide”, along with some other patterns I am working on. I’ve taken the pattern descriptions from the book “Enterprise Integration Patterns” by Gregor Hohpe. I bought a copy of the book in 2004, and recently dusted it off when I started to look at implementing the patterns on the Windows Azure Service Bus. Gregor has also presented an session in 2011 “Enterprise Integration Patterns: Past, Present and Future” which is well worth a look. I’ll be covering more patterns in the coming weeks, I’m currently working on Wire-Tap and Scatter-Gather. There will no doubt be a section on implementing these patterns in my “SOA, Connectivity and Integration using the Windows Azure Service Bus” course. There are a number of scenarios where a message needs to be divided into a number of sub messages, and also where a number of sub messages need to be combined to form one message. The splitter and aggregator patterns provide a definition of how this can be achieved. This section will focus on the implementation of basic splitter and aggregator patens using the Windows Azure Service Bus direct programming model. In BizTalk Server receive pipelines are typically used to implement the splitter patterns, with sequential convoy orchestrations often used to aggregate messages. In the current release of the Service Bus, there is no functionality in the direct programming model that implements these patterns, so it is up to the developer to implement them in the applications that send and receive messages. Splitter A message splitter takes a message and spits the message into a number of sub messages. As there are different scenarios for how a message can be split into sub messages, message splitters are implemented using different algorithms. The Enterprise Integration Patterns book describes the splatter pattern as follows: How can we process a message if it contains multiple elements, each of which may have to be processed in a different way? Use a Splitter to break out the composite message into a series of individual messages, each containing data related to one item. The Enterprise Integration Patterns website provides a description of the Splitter pattern here. In some scenarios a batch message could be split into the sub messages that are contained in the batch. The splitting of a message could be based on the message type of sub-message, or the trading partner that the sub message is to be sent to. Aggregator An aggregator takes a stream or related messages and combines them together to form one message. The Enterprise Integration Patterns book describes the aggregator pattern as follows: How do we combine the results of individual, but related messages so that they can be processed as a whole? Use a stateful filter, an Aggregator, to collect and store individual messages until a complete set of related messages has been received. Then, the Aggregator publishes a single message distilled from the individual messages. The Enterprise Integration Patterns website provides a description of the Aggregator pattern here. A common example of the need for an aggregator is in scenarios where a stream of messages needs to be combined into a daily batch to be sent to a legacy line-of-business application. The BizTalk Server EDI functionality provides support for batching messages in this way using a sequential convoy orchestration. Scenario The scenario for this implementation of the splitter and aggregator patterns is the sending and receiving of large messages using a Service Bus queue. In the current release, the Windows Azure Service Bus currently supports a maximum message size of 256 KB, with a maximum header size of 64 KB. This leaves a safe maximum body size of 192 KB. The BrokeredMessage class will support messages larger than 256 KB; in fact the Size property is of type long, implying that very large messages may be supported at some point in the future. The 256 KB size restriction is set in the service bus components that are deployed in the Windows Azure data centers. One of the ways of working around this size restriction is to split large messages into a sequence of smaller sub messages in the sending application, send them via a queue, and then reassemble them in the receiving application. This scenario will be used to demonstrate the pattern implementations. Implementation The splitter and aggregator will be used to provide functionality to send and receive large messages over the Windows Azure Service Bus. In order to make the implementations generic and reusable they will be implemented as a class library. The splitter will be implemented in the LargeMessageSender class and the aggregator in the LargeMessageReceiver class. A class diagram showing the two classes is shown below. Implementing the Splitter The splitter will take a large brokered message, and split the messages into a sequence of smaller sub-messages that can be transmitted over the service bus messaging entities. The LargeMessageSender class provides a Send method that takes a large brokered message as a parameter. The implementation of the class is shown below; console output has been added to provide details of the splitting operation. public class LargeMessageSender {     private static int SubMessageBodySize = 192 * 1024;     private QueueClient m_QueueClient;       public LargeMessageSender(QueueClient queueClient)     {         m_QueueClient = queueClient;     }       public void Send(BrokeredMessage message)     {         // Calculate the number of sub messages required.         long messageBodySize = message.Size;         int nrSubMessages = (int)(messageBodySize / SubMessageBodySize);         if (messageBodySize % SubMessageBodySize != 0)         {             nrSubMessages++;         }           // Create a unique session Id.         string sessionId = Guid.NewGuid().ToString();         Console.WriteLine("Message session Id: " + sessionId);         Console.Write("Sending {0} sub-messages", nrSubMessages);           Stream bodyStream = message.GetBody<Stream>();         for (int streamOffest = 0; streamOffest < messageBodySize;             streamOffest += SubMessageBodySize)         {                                     // Get the stream chunk from the large message             long arraySize = (messageBodySize - streamOffest) > SubMessageBodySize                 ? SubMessageBodySize : messageBodySize - streamOffest;             byte[] subMessageBytes = new byte[arraySize];             int result = bodyStream.Read(subMessageBytes, 0, (int)arraySize);             MemoryStream subMessageStream = new MemoryStream(subMessageBytes);               // Create a new message             BrokeredMessage subMessage = new BrokeredMessage(subMessageStream, true);             subMessage.SessionId = sessionId;               // Send the message             m_QueueClient.Send(subMessage);             Console.Write(".");         }         Console.WriteLine("Done!");     }} The LargeMessageSender class is initialized with a QueueClient that is created by the sending application. When the large message is sent, the number of sub messages is calculated based on the size of the body of the large message. A unique session Id is created to allow the sub messages to be sent as a message session, this session Id will be used for correlation in the aggregator. A for loop in then used to create the sequence of sub messages by creating chunks of data from the stream of the large message. The sub messages are then sent to the queue using the QueueClient. As sessions are used to correlate the messages, the queue used for message exchange must be created with the RequiresSession property set to true. Implementing the Aggregator The aggregator will receive the sub messages in the message session that was created by the splitter, and combine them to form a single, large message. The aggregator is implemented in the LargeMessageReceiver class, with a Receive method that returns a BrokeredMessage. The implementation of the class is shown below; console output has been added to provide details of the splitting operation.   public class LargeMessageReceiver {     private QueueClient m_QueueClient;       public LargeMessageReceiver(QueueClient queueClient)     {         m_QueueClient = queueClient;     }       public BrokeredMessage Receive()     {         // Create a memory stream to store the large message body.         MemoryStream largeMessageStream = new MemoryStream();           // Accept a message session from the queue.         MessageSession session = m_QueueClient.AcceptMessageSession();         Console.WriteLine("Message session Id: " + session.SessionId);         Console.Write("Receiving sub messages");           while (true)         {             // Receive a sub message             BrokeredMessage subMessage = session.Receive(TimeSpan.FromSeconds(5));               if (subMessage != null)             {                 // Copy the sub message body to the large message stream.                 Stream subMessageStream = subMessage.GetBody<Stream>();                 subMessageStream.CopyTo(largeMessageStream);                   // Mark the message as complete.                 subMessage.Complete();                 Console.Write(".");             }             else             {                 // The last message in the sequence is our completeness criteria.                 Console.WriteLine("Done!");                 break;             }         }                     // Create an aggregated message from the large message stream.         BrokeredMessage largeMessage = new BrokeredMessage(largeMessageStream, true);         return largeMessage;     } }   The LargeMessageReceiver initialized using a QueueClient that is created by the receiving application. The receive method creates a memory stream that will be used to aggregate the large message body. The AcceptMessageSession method on the QueueClient is then called, which will wait for the first message in a message session to become available on the queue. As the AcceptMessageSession can throw a timeout exception if no message is available on the queue after 60 seconds, a real-world implementation should handle this accordingly. Once the message session as accepted, the sub messages in the session are received, and their message body streams copied to the memory stream. Once all the messages have been received, the memory stream is used to create a large message, that is then returned to the receiving application. Testing the Implementation The splitter and aggregator are tested by creating a message sender and message receiver application. The payload for the large message will be one of the webcast video files from http://www.cloudcasts.net/, the file size is 9,697 KB, well over the 256 KB threshold imposed by the Service Bus. As the splitter and aggregator are implemented in a separate class library, the code used in the sender and receiver console is fairly basic. The implementation of the main method of the sending application is shown below.   static void Main(string[] args) {     // Create a token provider with the relevant credentials.     TokenProvider credentials =         TokenProvider.CreateSharedSecretTokenProvider         (AccountDetails.Name, AccountDetails.Key);       // Create a URI for the serivce bus.     Uri serviceBusUri = ServiceBusEnvironment.CreateServiceUri         ("sb", AccountDetails.Namespace, string.Empty);       // Create the MessagingFactory     MessagingFactory factory = MessagingFactory.Create(serviceBusUri, credentials);       // Use the MessagingFactory to create a queue client     QueueClient queueClient = factory.CreateQueueClient(AccountDetails.QueueName);       // Open the input file.     FileStream fileStream = new FileStream(AccountDetails.TestFile, FileMode.Open);       // Create a BrokeredMessage for the file.     BrokeredMessage largeMessage = new BrokeredMessage(fileStream, true);       Console.WriteLine("Sending: " + AccountDetails.TestFile);     Console.WriteLine("Message body size: " + largeMessage.Size);     Console.WriteLine();         // Send the message with a LargeMessageSender     LargeMessageSender sender = new LargeMessageSender(queueClient);     sender.Send(largeMessage);       // Close the messaging facory.     factory.Close();  } The implementation of the main method of the receiving application is shown below. static void Main(string[] args) {       // Create a token provider with the relevant credentials.     TokenProvider credentials =         TokenProvider.CreateSharedSecretTokenProvider         (AccountDetails.Name, AccountDetails.Key);       // Create a URI for the serivce bus.     Uri serviceBusUri = ServiceBusEnvironment.CreateServiceUri         ("sb", AccountDetails.Namespace, string.Empty);       // Create the MessagingFactory     MessagingFactory factory = MessagingFactory.Create(serviceBusUri, credentials);       // Use the MessagingFactory to create a queue client     QueueClient queueClient = factory.CreateQueueClient(AccountDetails.QueueName);       // Create a LargeMessageReceiver and receive the message.     LargeMessageReceiver receiver = new LargeMessageReceiver(queueClient);     BrokeredMessage largeMessage = receiver.Receive();       Console.WriteLine("Received message");     Console.WriteLine("Message body size: " + largeMessage.Size);       string testFile = AccountDetails.TestFile.Replace(@"\In\", @"\Out\");     Console.WriteLine("Saving file: " + testFile);       // Save the message body as a file.     Stream largeMessageStream = largeMessage.GetBody<Stream>();     largeMessageStream.Seek(0, SeekOrigin.Begin);     FileStream fileOut = new FileStream(testFile, FileMode.Create);     largeMessageStream.CopyTo(fileOut);     fileOut.Close();       Console.WriteLine("Done!"); } In order to test the application, the sending application is executed, which will use the LargeMessageSender class to split the message and place it on the queue. The output of the sender console is shown below. The console shows that the body size of the large message was 9,929,365 bytes, and the message was sent as a sequence of 51 sub messages. When the receiving application is executed the results are shown below. The console application shows that the aggregator has received the 51 messages from the message sequence that was creating in the sending application. The messages have been aggregated to form a massage with a body of 9,929,365 bytes, which is the same as the original large message. The message body is then saved as a file. Improvements to the Implementation The splitter and aggregator patterns in this implementation were created in order to show the usage of the patterns in a demo, which they do quite well. When implementing these patterns in a real-world scenario there are a number of improvements that could be made to the design. Copying Message Header Properties When sending a large message using these classes, it would be great if the message header properties in the message that was received were copied from the message that was sent. The sending application may well add information to the message context that will be required in the receiving application. When the sub messages are created in the splitter, the header properties in the first message could be set to the values in the original large message. The aggregator could then used the values from this first sub message to set the properties in the message header of the large message during the aggregation process. Using Asynchronous Methods The current implementation uses the synchronous send and receive methods of the QueueClient class. It would be much more performant to use the asynchronous methods, however doing so may well affect the sequence in which the sub messages are enqueued, which would require the implementation of a resequencer in the aggregator to restore the correct message sequence. Handling Exceptions In order to keep the code readable no exception handling was added to the implementations. In a real-world scenario exceptions should be handled accordingly.

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• Running OpenStack Icehouse with ZFS Storage Appliance

  - by Ronen Kofman

  Couple of months ago Oracle announced the support for OpenStack Cinder plugin with ZFS Storage Appliance (aka ZFSSA).  With our recent release of the Icehouse tech preview I thought it is a good opportunity to demonstrate the ZFSSA plugin working with Icehouse. One thing that helps a lot to get started with ZFSSA is that it has a VirtualBox simulator. This simulator allows users to try out the appliance’s features before getting to a real box. Users can test the functionality and design an environment even before they have a real appliance which makes the deployment process much more efficient. With OpenStack this is especially nice because having a simulator on the other end allows us to test the complete set of the Cinder plugin and check the entire integration on a single server or even a laptop. Let’s see how this works Installing and Configuring the Simulator To get started we first need to download the simulator, the simulator is available here, unzip it and it is ready to be imported to VirtualBox. If you do not already have VirtualBox installed you can download it from here according to your platform of choice. To import the simulator go to VirtualBox console File -> Import Appliance , navigate to the location of the simulator and import the virtual machine. When opening the virtual machine you will need to make the following changes: - Network – by default the network is “Host Only” , the user needs to change that to “Bridged” so the VM can connect to the network and be accessible. - Memory (optional) – the VM comes with a default of 2560MB which may be fine but if you have more memory that could not hurt, in my case I decided to give it 8192 - vCPU (optional) – the default the VM comes with 1 vCPU, I decided to change it to two, you are welcome to do so too. And here is how the VM looks like: Start the VM, when the boot process completes we will need to change the root password and the simulator is running and ready to go. Now that the simulator is up and running we can access simulated appliance using the URL https://<IP or DNS name>:215/, the IP is showing on the virtual machine console. At this stage we will need to configure the appliance, in my case I did not change any of the default (in other words pressed ‘commit’ several times) and the simulated appliance was configured and ready to go. We will need to enable REST access otherwise Cinder will not be able to call the appliance we do that in Configuration->Services and at the end of the page there is ‘REST’ button, enable it. If you are a more advanced user you can set additional features in the appliance but for the purpose of this demo this is sufficient. One final step will be to create a pool, go to Configuration -> Storage and add a pool as shown below the pool is named “default”: The simulator is now running, configured and ready for action. Configuring Cinder Back to OpenStack, I have a multi node deployment which we created according to the “Getting Started with Oracle VM, Oracle Linux and OpenStack” guide using Icehouse tech preview release. Now we need to install and configure the ZFSSA Cinder plugin using the README file. In short the steps are as follows: 1. Copy the file from here to the control node and place them at: /usr/lib/python2.6/site-packages/cinder/volume/drivers/zfssa 2. Configure the plugin, editing /etc/cinder/cinder.conf # Driver to use for volume creation (string value) #volume_driver=cinder.volume.drivers.lvm.LVMISCSIDriver volume_driver=cinder.volume.drivers.zfssa.zfssaiscsi.ZFSSAISCSIDriver zfssa_host = <HOST IP> zfssa_auth_user = root zfssa_auth_password = <ROOT PASSWORD> zfssa_pool = default zfssa_target_portal = <HOST IP>:3260 zfssa_project = test zfssa_initiator_group = default zfssa_target_interfaces = e1000g0 3. Restart the cinder-volume service: service openstack-cinder-volume restart 4. Look into the log file, this will tell us if everything works well so far. If you see any errors fix them before continuing. 5. Install iscsi-initiator-utils package, this is important since the plugin uses iscsi commands from this package: yum install -y iscsi-initiator-utils The installation and configuration are very simple, we do not need to have a “project” in the ZFSSA but we do need to define a pool. Creating and Using Volumes in OpenStack We are now ready to work, to get started lets create a volume in OpenStack and see it showing up on the simulator: #  cinder create 2 --display-name my-volume-1 +---------------------+--------------------------------------+ |       Property      |                Value                 | +---------------------+--------------------------------------+ |     attachments     |                  []                  | |  availability_zone  |                 nova                 | |       bootable      |                false                 | |      created_at     |      2014-08-12T04:24:37.806752      | | display_description |                 None                 | |     display_name    |             my-volume-1              | |      encrypted      |                False                 | |          id         | df67c447-9a36-4887-a8ff-74178d5d06ee | |       metadata      |                  {}                  | |         size        |                  2                   | |     snapshot_id     |                 None                 | |     source_volid    |                 None                 | |        status       |               creating               | |     volume_type     |                 None                 | +---------------------+--------------------------------------+ In the simulator: Extending the volume to 5G: # cinder extend df67c447-9a36-4887-a8ff-74178d5d06ee 5 In the simulator: Creating templates using Cinder Volumes By default OpenStack supports ephemeral storage where an image is copied into the run area during instance launch and deleted when the instance is terminated. With Cinder we can create persistent storage and launch instances from a Cinder volume. Booting from volume has several advantages, one of the main advantages of booting from volumes is speed. No matter how large the volume is the launch operation is immediate there is no copying of an image to a run areas, an operation which can take a long time when using ephemeral storage (depending on image size). In this deployment we have a Glance image of Oracle Linux 6.5, I would like to make it into a volume which I can boot from. When creating a volume from an image we actually “download” the image into the volume and making the volume bootable, this process can take some time depending on the image size, during the download we will see the following status: # cinder create --image-id 487a0731-599a-499e-b0e2-5d9b20201f0f --display-name ol65 2 # cinder list +--------------------------------------+-------------+--------------+------+-------------+ |                  ID                  |    Status   | Display Name | Size | Volume Type | … +--------------------------------------+-------------+--------------+------+------------- | df67c447-9a36-4887-a8ff-74178d5d06ee |  available  | my-volume-1  |  5   |     None    | … | f61702b6-4204-4f10-8bdf-7da792f15c28 | downloading |     ol65     |  2   |     None    | … +--------------------------------------+-------------+--------------+------+-------------+ After the download is complete we will see that the volume status changed to “available” and that the bootable state is “true”. We can use this new volume to boot an instance from or we can use it as a template. Cinder can create a volume from another volume and ZFSSA can replicate volumes instantly in the back end. The result is an efficient template model where users can spawn an instance from a “template” instantly even if the template is very large in size. Let’s try replicating the bootable volume with the Oracle Linux 6.5 on it creating additional 3 bootable volumes: # cinder create 2 --source-volid f61702b6-4204-4f10-8bdf-7da792f15c28 --display-name ol65-bootable-1 # cinder create 2 --source-volid f61702b6-4204-4f10-8bdf-7da792f15c28 --display-name ol65-bootable-2 # cinder create 2 --source-volid f61702b6-4204-4f10-8bdf-7da792f15c28 --display-name ol65-bootable-3 # cinder list +--------------------------------------+-----------+-----------------+------+-------------+----------+-------------+ |                  ID                  |   Status  |   Display Name  | Size | Volume Type | Bootable | Attached to | +--------------------------------------+-----------+-----------------+------+-------------+----------+-------------+ | 9bfe0deb-b9c7-4d97-8522-1354fc533c26 | available | ol65-bootable-2 |  2   |     None    |   true   |             | | a311a855-6fb8-472d-b091-4d9703ef6b9a | available | ol65-bootable-1 |  2   |     None    |   true   |             | | df67c447-9a36-4887-a8ff-74178d5d06ee | available |   my-volume-1   |  5   |     None    |  false   |             | | e7fbd2eb-e726-452b-9a88-b5eee0736175 | available | ol65-bootable-3 |  2   |     None    |   true   |             | | f61702b6-4204-4f10-8bdf-7da792f15c28 | available |       ol65      |  2   |     None    |   true   |             | +--------------------------------------+-----------+-----------------+------+-------------+----------+-------------+ Note that the creation of those 3 volume was almost immediate, no need to download or copy, ZFSSA takes care of the volume copy for us. Start 3 instances: # nova boot --boot-volume a311a855-6fb8-472d-b091-4d9703ef6b9a --flavor m1.tiny ol65-instance-1 --nic net-id=25b19746-3aea-4236-8193-4c6284e76eca # nova boot --boot-volume 9bfe0deb-b9c7-4d97-8522-1354fc533c26 --flavor m1.tiny ol65-instance-2 --nic net-id=25b19746-3aea-4236-8193-4c6284e76eca # nova boot --boot-volume e7fbd2eb-e726-452b-9a88-b5eee0736175 --flavor m1.tiny ol65-instance-3 --nic net-id=25b19746-3aea-4236-8193-4c6284e76eca Instantly replicating volumes is a very powerful feature, especially for large templates. The ZFSSA Cinder plugin allows us to take advantage of this feature of ZFSSA. By offloading some of the operations to the array OpenStack create a highly efficient environment where persistent volume can be instantly created from a template. That’s all for now, with this environment you can continue to test ZFSSA with OpenStack and when you are ready for the real appliance the operations will look the same. @RonenKofman

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• Office 2010: It&rsquo;s not just DOC(X) and XLS(X)

  - by andrewbrust

  Office 2010 has released to manufacturing.  The bits have left the (product team’s) building.  Will you upgrade? This version of Office is officially numbered 14, a designation that correlates with the various releases, through the years, of Microsoft Word.  There were six major versions of Word for DOS, during whose release cycles came three 16-bit Windows versions.  Then, starting with Word 95 and counting through Word 2007, there have been six more versions – all for the 32-bit Windows platform.  Skip version 13 to ward off folksy bad luck (and, perhaps, the bugs that could come with it) and that brings us to version 14, which includes implementations for both 32- and 64-bit Windows platforms.  We’ve come a long way baby.  Or have we? As it does every three years or so, debate will now start to rage on over whether we need a “14th” version the PC platform’s standard word processor, or a “13th” version of the spreadsheet.  If you accept the premise of that question, then you may be on a slippery slope toward answering it in the negative.  Thing is, that premise is valid for certain customers and not others. The Microsoft Office product has morphed from one that offered core word processing, spreadsheet, presentation and email functionality to a suite of applications that provides unique, new value-added features, and even whole applications, in the context of those core services.  The core apps thus grow in mission: Excel is a BI tool.  Word is a collaborative editorial system for the production of publications.  PowerPoint is a media production platform for for live presentations and, increasingly, for delivering more effective presentations online.  Outlook is a time and task management system.  Access is a rich client front-end for data-driven self-service SharePoint applications.  OneNote helps you capture ideas, corral random thoughts in a semi-structured way, and then tie them back to other, more rigidly structured, Office documents. Google Docs and other cloud productivity platforms like Zoho don’t really do these things.  And there is a growing chorus of voices who say that they shouldn’t, because those ancillary capabilities are over-engineered, over-produced and “under-necessary.”  They might say Microsoft is layering on superfluous capabilities to avoid admitting that Office’s core capabilities, the ones people really need, have become commoditized. It’s hard to take sides in that argument, because different people, and the different companies that employ them, have different needs.  For my own needs, it all comes down to three basic questions: will the new version of Office save me time, will it make the mundane parts of my job easier, and will it augment my services to customers?  I need my time back.  I need to spend more of it with my family, and more of it focusing on my own core capabilities rather than the administrative tasks around them.  And I also need my customers to be able to get more value out of the services I provide. Help me triage my inbox, help me get proposals done more quickly and make them easier to read.  Let me get my presentations done faster, make them more effective and make it easier for me to reuse materials from other presentations.  And, since I’m in the BI and data business, help me and my customers manage data and analytics more easily, both on the desktop and online. Those are my criteria.  And, with those in mind, Office 2010 is looking like a worthwhile upgrade.  Perhaps it’s not earth-shattering, but it offers a combination of incremental improvements and a few new major capabilities that I think are quite compelling.  I provide a brief roundup of them here.  It’s admittedly arbitrary and not comprehensive, but I think it tells the Office 2010 story effectively. Across the Suite More than any other, this release of Office aims to give collaboration a real workout.  In certain apps, for the first time, documents can be opened simultaneously by multiple users, with colleagues’ changes appearing in near real-time.  Web-browser-based versions of Word, Excel, PowerPoint and OneNote will be available to extend collaboration to contributors who are off the corporate network. The ribbon user interface is now more pervasive (for example, it appears in OneNote and in Outlook’s main window).  It’s also customizable, allowing users to add, easily, buttons and options of their choosing, into new tabs, or into new groups within existing tabs. Microsoft has also taken the File menu (which was the “Office Button” menu in the 2007 release) and made it into a full-screen “Backstage” view where document-wide operations, like saving, printing and online publishing are performed. And because, more and more, heavily formatted content is cut and pasted between documents and applications, Office 2010 makes it easier to manage the retention or jettisoning of that formatting right as the paste operation is performed.  That’s much nicer than stripping it off, or adding it back, afterwards. And, speaking of pasting, a number of Office apps now make it especially easy to insert screenshots within their documents.  I know that’s useful to me, because I often document or critique applications and need to show them in action.  For the vast majority of users, I expect that this feature will be more useful for capturing snapshots of Web pages, but we’ll have to see whether this feature becomes popular.   Excel At first glance, Excel 2010 looks and acts nearly identically to the 2007 version.  But additional glances are necessary.  It’s important to understand that lots of people in the working world use Excel as more of a database, analytics and mathematical modeling tool than merely as a spreadsheet.  And it’s also important to understand that Excel wasn’t designed to handle such workloads past a certain scale.  That all changes with this release. The first reason things change is that Excel has been tuned for performance.  It’s been optimized for multi-threaded operation; previously lengthy processes have been shortened, especially for large data sets; more rows and columns are allowed and, for the first time, Excel (and the rest of Office) is available in a 64-bit version.  For Excel, this means users can take advantage of more than the 2GB of memory that the 32-bit version is limited to. On the analysis side, Excel 2010 adds Sparklines (tiny charts that fit into a single cell and can therefore be presented down an entire column or across a row) and Slicers (a more user-friendly filter mechanism for PivotTables and charts, which visually indicates what the filtered state of a given data member is).  But most important, Excel 2010 supports the new PowerPIvot add-in which brings true self-service BI to Office.  PowerPivot allows users to import data from almost anywhere, model it, and then analyze it.  Rather than forcing users to build “spreadmarts” or use corporate-built data warehouses, PowerPivot models function as true columnar, in-memory OLAP cubes that can accommodate millions of rows of data and deliver fast drill-down performance. And speaking of OLAP, Excel 2010 now supports an important Analysis Services OLAP feature called write-back.  Write-back is especially useful in financial forecasting scenarios for which Excel is the natural home.  Support for write-back is long overdue, but I’m still glad it’s there, because I had almost given up on it.   PowerPoint This version of PowerPoint marks its progression from a presentation tool to a video and photo editing and production tool.  Whether or not it’s successful in this pursuit, and if offering this is even a sensible goal, is another question. Regardless, the new capabilities are kind of interesting.  A greatly enhanced set of slide transitions with 3D effects; in-product photo and video editing; accommodation of embedded videos from services such as YouTube; and the ability to save a presentation as a video each lay testimony to PowerPoint’s transformation into a media tool and away from a pure presentation tool. These capabilities also recognize the importance of the Web as both a source for materials and a channel for disseminating PowerPoint output. Congruent with that is PowerPoint’s new ability to broadcast a slide presentation, using a quickly-generated public URL, without involving the hassle or expense of a Web meeting service like GoToMeeting or Microsoft’s own LiveMeeting.  Slides presented through this broadcast feature retain full color fidelity and transitions and animations are preserved as well.   Outlook Microsoft’s ubiquitous email/calendar/contact/task management tool gains long overdue speed improvements, especially against POP3 email accounts.  Outlook 2010 also supports multiple Exchange accounts, rather than just one; tighter integration with OneNote; and a new Social Connector providing integration with, and presence information from, online social network services like LinkedIn and Facebook (not to mention Windows Live).  A revamped conversation view now includes messages that are part of a given thread regardless of which folder they may be stored in. I don’t know yet how well the Social Connector will work or whether it will keep Outlook relevant to those who live on Facebook and LinkedIn.  But among the other features, there’s very little not to like.   OneNote To me, OneNote is the part of Office that just keeps getting better.  There is one major caveat to this, which I’ll cover in a moment, but let’s first catalog what new stuff OneNote 2010 brings.  The best part of OneNote, is the way each of its versions have managed hierarchy: Notebooks have sections, sections have pages, pages have sub pages, multiple notes can be contained in either, and each note supports infinite levels of indentation.  None of that is new to 2010, but the new version does make creation of pages and subpages easier and also makes simple work out of promoting and demoting pages from sub page to full page status.  And relationships between pages are quite easy to create now: much like a Wiki, simply typing a page’s name in double-square-brackets (“[[…]]”) creates a link to it. OneNote is also great at integrating content outside of its notebooks.  With a new Dock to Desktop feature, OneNote becomes aware of what window is displayed in the rest of the screen and, if it’s an Office document or a Web page, links the notes you’re typing, at the time, to it.  A single click from your notes later on will bring that same document or Web page back on-screen.  Embedding content from Web pages and elsewhere is also easier.  Using OneNote’s Windows Key+S combination to grab part of the screen now allows you to specify the destination of that bitmap instead of automatically creating a new note in the Unfiled Notes area.  Using the Send to OneNote buttons in Internet Explorer and Outlook result in the same choice. Collaboration gets better too.  Real-time multi-author editing is better accommodated and determining author lineage of particular changes is easily carried out. My one pet peeve with OneNote is the difficulty using it when I’m not one a Windows PC.  OneNote’s main competitor, Evernote, while I believe inferior in terms of features, has client versions for PC, Mac, Windows Mobile, Android, iPhone, iPad and Web browsers.  Since I have an Android phone and an iPad, I am practically forced to use it.  However, the OneNote Web app should help here, as should a forthcoming version of OneNote for Windows Phone 7.  In the mean time, it turns out that using OneNote’s Email Page ribbon button lets you move a OneNote page easily into EverNote (since every EverNote account gets a unique email address for adding notes) and that Evernote’s Email function combined with Outlook’s Send to OneNote button (in the Move group of the ribbon’s Home tab) can achieve the reverse.   Access To me, the big change in Access 2007 was its tight integration with SharePoint lists.  Access 2010 and SharePoint 2010 continue this integration with the introduction of SharePoint’s Access Services.  Much as Excel Services provides a SharePoint-hosted experience for viewing (and now editing) Excel spreadsheet, PivotTable and chart content, Access Services allows for SharePoint browser-hosted editing of Access data within the forms that are built in the Access client itself. To me this makes all kinds of sense.  Although it does beg the question of where to draw the line between Access, InfoPath, SharePoint list maintenance and SharePoint 2010’s new Business Connectivity Services.  Each of these tools provide overlapping data entry and data maintenance functionality. But if you do prefer Access, then you’ll like  things like templates and application parts that make it easier to get off the blank page.  These features help you quickly get tables, forms and reports built out.  To make things look nice, Access even gets its own version of Excel’s Conditional Formatting feature, letting you add data bars and data-driven text formatting.   Word As I said at the beginning of this post, upgrades to Office are about much more than enhancing the suite’s flagship word processing application. So are there any enhancements in Word worth mentioning?  I think so.  The most important one has to be the collaboration features.  Essentially, when a user opens a Word document that is in a SharePoint document library (or Windows Live SkyDrive folder), rather than the whole document being locked, Word has the ability to observe more granular locks on the individual paragraphs being edited.  Word also shows you who’s editing what and its Save function morphs into a sync feature that both saves your changes and loads those made by anyone editing the document concurrently. There’s also a new navigation pane that lets you manage sections in your document in much the same way as you manage slides in a PowerPoint deck.  Using the navigation pane, you can reorder sections, insert new ones, or promote and demote sections in the outline hierarchy.  Not earth shattering, but nice.   Other Apps and Summarized Findings What about InfoPath, Publisher, Visio and Project?  I haven’t looked at them yet.  And for this post, I think that’s fine.  While those apps (and, arguably, Access) cater to specific tasks, I think the apps we’ve looked at in this post service the general purpose needs of most users.  And the theme in those 2010 apps is clear: collaboration is key, the Web and productivity are indivisible, and making data and analytics into a self-service amenity is the way to go.  But perhaps most of all, features are still important, as long as they get you through your day faster, rather than adding complexity for its own sake.  I would argue that this is true for just about every product Microsoft makes: users want utility, not complexity.

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• DD-WRT/openwrt question (TP-Link WR1043N)

  - by Shiki

  Can I squeeze more speed out of my router (when it comes to USB attached storage device on it) with open/DD wrt? (Sorry I don't really know such firmwares.) (Guess it works with ntfs-3g? I don't know.) Feel free to make this a real question. Basically the question: Does the change worth it in the terms of speed?

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• Difference between PC3-8500s and PC3-8500f

  - by Dan

  Is there any real difference between PC3-8500s and PC3-8500f? It's Laptop memory, DDR3. Would a laptop which can take one also be able to use the other? Thanks

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• Is there a Firefox addon to show unshortened URLs in a tooltip?

  - by Yuval

  I need a FF addon to do something like Unshorten and present the real URL in a tooltip. The addon should be FF3.6 compatible. Does anyone know if there is such an addon out there?

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• Unable to install ExchangeCdo with Outlook 2010

  - by MrStatic

  We recently got the Blackberry Express Server for our small home business and linked it in with our Exchange 2010 server. All is well except for calendar syncing. From what I can tell I require the ExchangeCdo patch. Except when I go to install it, it errors saying I require Outlook 2007. I have Outlook 2010 on the server and have no real way of getting 2007 on instead. Any suggestions?

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• Linux Skype alternative similar to Windows Skype?

  - by vsecades

  Does anybody know a good option for a Skype based solution that works on Linux? I have a real problem with the current Linux version as it is a crappy, buggy and downgraded version of the Windows equivalent. Help?

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• What is the difference between uninstalling a program through Control Panel, and uninstalling via th

  - by sunpech

  What is the difference between uninstalling a program through Control Panel, and uninstalling via the Program's uninstall.exe? Example: C:\Program Files (x86)\Notepad++\uninstall.exe In general, I read that it's better to uninstall a program via window's Control Panel. But for the programs that have their own uninstall.exe, is there any real difference between the un-installations? Is the Control Panel's cleaner in removing dependencies?

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• Outlook 2007 won't close

  - by Scott Weinstein

  I use Outlook 2007 at home as an IMAP client and RSS feed reader. I have a problem that when I close outlook, the window exits, but the process remains running. This prevents me from opening outlook again and on Win7 prevents rapid shutdown of my computer. How can I have Outlook 2007 exit for real? Edit: Here's what the addins dialog reports Active: None Inactive: MS Outlook Mobile Service, MS VBA for Outlook, OneNote Notes for Outlook Items, Outlook Change Notifier, Windows Search Email indexer.

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• SBS domain name choice

  - by sandymac

  We are about to set up SBS 2011 at my small company < 10 users. My collaborator wants to name the SBS domain "example.local" . I'm of the opinion we should name the SBS domain "corp.example.com" and setup DNS so the "corp" record is a NS record to the SBS server's private IP. FYI: "Example.com" isn't the real domain name and while the website is hosted outside our office, email will be stored on the SBS server in our office after passing though a spam filtering smart host hosted elsewhere too.

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• A scripting language for legacy hardware

  - by codeholic

  I want to pick up a scripting language for real legacy hardware. It must be compilable for 16-bit. What may suffice?

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• Website for facilitating interactive discussion ?

  - by shan23

  I had heard of websites that would allow two or more people to share a common text editor, so that changes to the text can be made and simultaneously viewed by all participants in real time - this kind of websites is ostensibly used for conducting interviews online. I know they exist (I had read of them in a tech magazine), but I can't seem to find the right search term for google to throw me a correct link. So, I'm asking you guys, as you might have used it before, or know what I'm talking about.

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• Who uses Zimbra Collaboration Suite and why?

  - by AlberT

  I am really curious about other people experiences and choices. After a long scouting, I found ZCS to be a really impressive solution, maybe the only real alternative to M$ Exchange. I'm very interested in opinions and case histories from users having already deployed Zimbra on their infrastructure or planning to do it. Both Community and Network edition cases are appreciated, pro and cons explained too :) Zimlets, addons, useful skins, Zimbra Desktop and other apps or mobile integration use case too of course.

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• PSTN Trunk TDM400P Install on Asterisk / Trixbox

  - by Jona

  Hey All, I'm trying to get a TDM400P card with FXO module to connect to our PSTN line. The card is correctly detected by Linux: [trixbox1.localdomain asterisk]# lspci 00:09.0 Communication controller: Tiger Jet Network Inc. Tiger3XX Modem/ISDN interface And asterisk can see the channel: > trixbox1*CLI> dahdi show channel 1 > Channel: 1LI> File Descriptor: 14 > Span: 11*CLI> Extension: I> Dialing: > noI> Context: from-pstn Caller ID: I> > Calling TON: 0 Caller ID name: > Mailbox: none Destroy: 0LI> InAlarm: > 1LI> Signalling Type: FXS Kewlstart > Radio: 0*CLI> Owner: <None> Real: > <None>> Callwait: <None> Threeway: > <None> Confno: -1LI> Propagated > Conference: -1 Real in conference: 0 > DSP: no1*CLI> Busy Detection: no TDD: > no1*CLI> Relax DTMF: no > Dialing/CallwaitCAS: 0/0 Default law: > ulaw Fax Handled: no Pulse phone: no > DND: no1*CLI> Echo Cancellation: > trixbox1128 taps trixbox1(unless TDM > bridged) currently OFF Actual > Confinfo: Num/0, Mode/0x0000 Actual > Confmute: No > Hookstate (FXS only): Onhook I have configured a "ZAP Trunk (DAHDI compatibility Mode)" with the ZAP identifier 1 and an outbound route, but when ever I try to make an external call via it I get the "All Circuits are busy now, please try your call again later message". The FXO module is directly connected to our phone line from BT via a BT-RJ11 cable. I'm guessing I've missed a configuration step somewhere but no idea where, any help greatly appreciated.

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• Windows Server traffic monitor that show traffic for each connected IP

  - by Mike Trader

  I would like to see traffic in bytes of individual users (IP's) in real time. Logging would be good too. Additionally I would like to see which process (CGI.exe, php script etc) they are connected to or minimally what the GET/POST request was. I have looked at many server monitoring tools but have not found something like this. Any suggestions would be appreciated.

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• Is quoted-printable enough to make a mail compliant with the line-length-restriction posed in RFC 2822?

  - by Mnementh

  In RFC 2822 (defining E-Mail) is defined, that no line SHOULD be longer than 78 chars (excluding CRLF) and MUST not longer than 998 characters. With quoted-printable longer lines will be broken into more lines, ending each with a '=' until the real linebreak is reached. Conforms a mail to the standard, if it contains lines longer than 78 (or 998) characters but is encoded with quoted-printable? There are arguments, that this isn't compliant, because the receiving mail-client has longer lines after decoding the quoted-printable message.

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• Can I use the character ñ in a sub-domain?

  - by nute

  We are launching our website in Spanish and are probably going to call it espanol.mydomain.com Since the real spelling is español, ideally we would allow people to type español.mydomain.com. Is that something that is possible today? Can we use this character in domains and sub-domains?

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• Cloning/copying traffic from production web cluster to test web cluster

  - by Marko Kevac

  Hello. We have 10 machine web cluster with approximately 1500 req/seq. How can we copy/clone all user traffic that comes to this production cluster in order to test new version of software, which is installed on a little bit smaller test cluster? It should be copy, not load balancing, i.e. real users must receive answer from production cluster, not testing one. OS: Linux Thanks.

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• How can I filter packets from a port monitor?

  - by engineerchuan

  I have some data going from Point A to Point B. I have a SPAN monitor set up to a monitoring device C. To recreate some real world scenarios, I want to filter out all traffic which is a certain type (H.323 VoIP Signaling Packets) so that C sees a subset of the information that is flowing from A to B. What would the easiest way to do this be? I assume I would need a computer with 2 NIC cards and some software to examine each packet and chuck out the H.323 VoIP packets? Thanks!

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• Why does limiting my virtual memory to 512MB with ulimit -v crash the JVM?

  - by Narinder Kumar

  I am trying to enforce maximum memory a program can consume on a Unix system. I thought ulimit -v should do the trick. Here is a sample Java program I have written for testing : import java.util.*; import java.io.*; public class EatMem { public static void main(String[] args) throws IOException, InterruptedException { System.out.println("Starting up..."); System.out.println("Allocating 128 MB of Memory"); List<byte[]> list = new LinkedList<byte[]>(); list.add(new byte[134217728]); //128 MB System.out.println("Done...."); } } By default, my ulimit settings are (output of ulimit -a) : core file size (blocks, -c) 0 data seg size (kbytes, -d) unlimited scheduling priority (-e) 0 file size (blocks, -f) unlimited pending signals (-i) 31398 max locked memory (kbytes, -l) 64 max memory size (kbytes, -m) unlimited open files (-n) 1024 pipe size (512 bytes, -p) 8 POSIX message queues (bytes, -q) 819200 real-time priority (-r) 0 stack size (kbytes, -s) 8192 cpu time (seconds, -t) unlimited max user processes (-u) 31398 virtual memory (kbytes, -v) unlimited file locks (-x) unlimited When I execute my java program (java EatMem), it executes without any problems. Now I try to limit max memory available to any program launched in the current shell to 512MB by launching the following command : ulimit -v 524288 ulimit -a output shows the limit to be set correctly (I suppose): core file size (blocks, -c) 0 data seg size (kbytes, -d) unlimited scheduling priority (-e) 0 file size (blocks, -f) unlimited pending signals (-i) 31398 max locked memory (kbytes, -l) 64 max memory size (kbytes, -m) unlimited open files (-n) 1024 pipe size (512 bytes, -p) 8 POSIX message queues (bytes, -q) 819200 real-time priority (-r) 0 stack size (kbytes, -s) 8192 cpu time (seconds, -t) unlimited max user processes (-u) 31398 virtual memory (kbytes, -v) 524288 file locks (-x) unlimited If I now try to execute my java program, it gives me the following error: Error occurred during initialization of VM Could not reserve enough space for object heap Could not create the Java virtual machine. Ideally it should not happen as my Java program is only taking around 128MB of memory which is well within my specified ulimit parameters. If I change the arguments to my Java program as below: java -Xmx256m EatMem The program again works fine. While trying to give more memory than limited by ulimit like : java -Xmx800m EatMem results in expected error. Why the program fails to execute in the first case after setting ulimit ? I have tried the above test on Ubuntu 11.10 and 12.0.4 with Java 1.6 and Java 7

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