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  • SQL SERVER – Concurrency Basics – Guest Post by Vinod Kumar

    - by pinaldave
    This guest post is by Vinod Kumar. Vinod Kumar has worked with SQL Server extensively since joining the industry over a decade ago. Working on various versions from SQL Server 7.0, Oracle 7.3 and other database technologies – he now works with the Microsoft Technology Center (MTC) as a Technology Architect. Let us read the blog post in Vinod’s own voice. Learning is always fun when it comes to SQL Server and learning the basics again can be more fun. I did write about Transaction Logs and recovery over my blogs and the concept of simplifying the basics is a challenge. In the real world we always see checks and queues for a process – say railway reservation, banks, customer supports etc there is a process of line and queue to facilitate everyone. Shorter the queue higher is the efficiency of system (a.k.a higher is the concurrency). Every database does implement this using checks like locking, blocking mechanisms and they implement the standards in a way to facilitate higher concurrency. In this post, let us talk about the topic of Concurrency and what are the various aspects that one needs to know about concurrency inside SQL Server. Let us learn the concepts as one-liners: Concurrency can be defined as the ability of multiple processes to access or change shared data at the same time. The greater the number of concurrent user processes that can be active without interfering with each other, the greater the concurrency of the database system. Concurrency is reduced when a process that is changing data prevents other processes from reading that data or when a process that is reading data prevents other processes from changing that data. Concurrency is also affected when multiple processes are attempting to change the same data simultaneously. Two approaches to managing concurrent data access: Optimistic Concurrency Model Pessimistic Concurrency Model Concurrency Models Pessimistic Concurrency Default behavior: acquire locks to block access to data that another process is using. Assumes that enough data modification operations are in the system that any given read operation is likely affected by a data modification made by another user (assumes conflicts will occur). Avoids conflicts by acquiring a lock on data being read so no other processes can modify that data. Also acquires locks on data being modified so no other processes can access the data for either reading or modifying. Readers block writer, writers block readers and writers. Optimistic Concurrency Assumes that there are sufficiently few conflicting data modification operations in the system that any single transaction is unlikely to modify data that another transaction is modifying. Default behavior of optimistic concurrency is to use row versioning to allow data readers to see the state of the data before the modification occurs. Older versions of the data are saved so a process reading data can see the data as it was when the process started reading and not affected by any changes being made to that data. Processes modifying the data is unaffected by processes reading the data because the reader is accessing a saved version of the data rows. Readers do not block writers and writers do not block readers, but, writers can and will block writers. Transaction Processing A transaction is the basic unit of work in SQL Server. Transaction consists of SQL commands that read and update the database but the update is not considered final until a COMMIT command is issued (at least for an explicit transaction: marked with a BEGIN TRAN and the end is marked by a COMMIT TRAN or ROLLBACK TRAN). Transactions must exhibit all the ACID properties of a transaction. ACID Properties Transaction processing must guarantee the consistency and recoverability of SQL Server databases. Ensures all transactions are performed as a single unit of work regardless of hardware or system failure. A – Atomicity C – Consistency I – Isolation D- Durability Atomicity: Each transaction is treated as all or nothing – it either commits or aborts. Consistency: ensures that a transaction won’t allow the system to arrive at an incorrect logical state – the data must always be logically correct.  Consistency is honored even in the event of a system failure. Isolation: separates concurrent transactions from the updates of other incomplete transactions. SQL Server accomplishes isolation among transactions by locking data or creating row versions. Durability: After a transaction commits, the durability property ensures that the effects of the transaction persist even if a system failure occurs. If a system failure occurs while a transaction is in progress, the transaction is completely undone, leaving no partial effects on data. Transaction Dependencies In addition to supporting all four ACID properties, a transaction might exhibit few other behaviors (known as dependency problems or consistency problems). Lost Updates: Occur when two processes read the same data and both manipulate the data, changing its value and then both try to update the original data to the new value. The second process might overwrite the first update completely. Dirty Reads: Occurs when a process reads uncommitted data. If one process has changed data but not yet committed the change, another process reading the data will read it in an inconsistent state. Non-repeatable Reads: A read is non-repeatable if a process might get different values when reading the same data in two reads within the same transaction. This can happen when another process changes the data in between the reads that the first process is doing. Phantoms: Occurs when membership in a set changes. It occurs if two SELECT operations using the same predicate in the same transaction return a different number of rows. Isolation Levels SQL Server supports 5 isolation levels that control the behavior of read operations. Read Uncommitted All behaviors except for lost updates are possible. Implemented by allowing the read operations to not take any locks, and because of this, it won’t be blocked by conflicting locks acquired by other processes. The process can read data that another process has modified but not yet committed. When using the read uncommitted isolation level and scanning an entire table, SQL Server can decide to do an allocation order scan (in page-number order) instead of a logical order scan (following page pointers). If another process doing concurrent operations changes data and move rows to a new location in the table, the allocation order scan can end up reading the same row twice. Also can happen if you have read a row before it is updated and then an update moves the row to a higher page number than your scan encounters later. Performing an allocation order scan under Read Uncommitted can cause you to miss a row completely – can happen when a row on a high page number that hasn’t been read yet is updated and moved to a lower page number that has already been read. Read Committed Two varieties of read committed isolation: optimistic and pessimistic (default). Ensures that a read never reads data that another application hasn’t committed. If another transaction is updating data and has exclusive locks on data, your transaction will have to wait for the locks to be released. Your transaction must put share locks on data that are visited, which means that data might be unavailable for others to use. A share lock doesn’t prevent others from reading but prevents them from updating. Read committed (snapshot) ensures that an operation never reads uncommitted data, but not by forcing other processes to wait. SQL Server generates a version of the changed row with its previous committed values. Data being changed is still locked but other processes can see the previous versions of the data as it was before the update operation began. Repeatable Read This is a Pessimistic isolation level. Ensures that if a transaction revisits data or a query is reissued the data doesn’t change. That is, issuing the same query twice within a transaction cannot pickup any changes to data values made by another user’s transaction because no changes can be made by other transactions. However, this does allow phantom rows to appear. Preventing non-repeatable read is a desirable safeguard but cost is that all shared locks in a transaction must be held until the completion of the transaction. Snapshot Snapshot Isolation (SI) is an optimistic isolation level. Allows for processes to read older versions of committed data if the current version is locked. Difference between snapshot and read committed has to do with how old the older versions have to be. It’s possible to have two transactions executing simultaneously that give us a result that is not possible in any serial execution. Serializable This is the strongest of the pessimistic isolation level. Adds to repeatable read isolation level by ensuring that if a query is reissued rows were not added in the interim, i.e, phantoms do not appear. Preventing phantoms is another desirable safeguard, but cost of this extra safeguard is similar to that of repeatable read – all shared locks in a transaction must be held until the transaction completes. In addition serializable isolation level requires that you lock data that has been read but also data that doesn’t exist. Ex: if a SELECT returned no rows, you want it to return no. rows when the query is reissued. This is implemented in SQL Server by a special kind of lock called the key-range lock. Key-range locks require that there be an index on the column that defines the range of values. If there is no index on the column, serializable isolation requires a table lock. Gets its name from the fact that running multiple serializable transactions at the same time is equivalent of running them one at a time. Now that we understand the basics of what concurrency is, the subsequent blog posts will try to bring out the basics around locking, blocking, deadlocks because they are the fundamental blocks that make concurrency possible. Now if you are with me – let us continue learning for SQL Server Locking Basics. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Concurrency

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  • Live Updates in PrimeFaces Line Chart

    - by Geertjan
    In the Facelets file: <p:layoutUnit position="center"> <h:form> <p:poll interval="3" update=":chartPanel" autoStart="true" /> </h:form> <p:panelGrid columns="1" id="chartPanel"> <p:lineChart xaxisLabel="Time" yaxisLabel="Position" value="#{chartController.linearModel}" legendPosition="nw" animate="true" style="height:400px;width: 1000px;"/> </p:panelGrid> </p:layoutUnit> The controler: import java.io.Serializable; import javax.inject.Named; import org.primefaces.model.chart.CartesianChartModel; import org.primefaces.model.chart.ChartSeries; @Named public class ChartController implements Serializable { private CartesianChartModel model; private ChartSeries data; public ChartController() { createLinearModel(); } private void createLinearModel() { model = new CartesianChartModel(); model.addSeries(getStockChartData("Stock Chart")); } private ChartSeries getStockChartData(String label) { data = new ChartSeries(); data.setLabel(label); for (int i = 1; i <= 20; i++) { data.getData().put(i, (int) (Math.random() * 1000)); } return data; } public CartesianChartModel getLinearModel() { return model; } } Based on this sample.

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  • Save blob to DB using hibernate

    - by Link123
    Hey! I tried save file to MySQL using blob with hibernate3. But I always have java.lang.UnsupportedOperationException: Blob may not be manipulated from creating session org.hibernate.lob.BlobImpl.excep(BlobImpl.java:127) Here some code. package com.uni.domain; public class File extends Identifier { private byte[] data; private String contentType; public byte[] getData() { return data; } public File() {} public void setData(byte[] photo) { this.data = photo; } public boolean isNew() { return true; } public String getContentType() { return contentType; } public void setContentType(String contentType) { this.contentType = contentType; } } package com.uni.domain; import org.hibernate.Hibernate; import org.hibernate.HibernateException; import org.hibernate.usertype.UserType; import java.io.InputStream; import java.io.OutputStream; import java.io.Serializable; import java.sql.*; import java.util.Arrays; public class PhotoType implements UserType { public int[] sqlTypes() { return new int[]{Types.BLOB}; } public Class returnedClass() { return byte[].class; } public boolean equals(Object o, Object o1) throws HibernateException { return Arrays.equals((byte[]) o, (byte[]) o1); } public int hashCode(Object o) throws HibernateException { return o.hashCode(); } public Object nullSafeGet(ResultSet resultSet, String[] strings, Object o) throws HibernateException, SQLException { Blob blob = resultSet.getBlob(strings[0]); return blob.getBytes(1, (int) blob.length()); } public void nullSafeSet(PreparedStatement st, Object value, int index) throws HibernateException, SQLException { st.setBlob(index, Hibernate.createBlob((byte[]) value)); } public Object deepCopy(Object value) { if (value == null) return null; byte[] bytes = (byte[]) value; byte[] result = new byte[bytes.length]; System.arraycopy(bytes, 0, result, 0, bytes.length); return result; } public boolean isMutable() { return true; } public Serializable disassemble(Object o) throws HibernateException { return null; . } public Object assemble(Serializable serializable, Object o) throws HibernateException { return null; . } public Object replace(Object o, Object o1, Object o2) throws HibernateException { return null; . } <?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE hibernate-mapping PUBLIC "-//Hibernate/Hibernate Mapping DTD 3.0//EN" "http://hibernate.sourceforge.net/hibernate-mapping-3.0.dtd"> <hibernate-mapping package="com.uni.domain"> <class name="com.uni.domain.File"> <id name="id"> <generator class="native"/> </id> <property name="data" type="com.uni.domain.FleType"/> <property name="contentType"/> </class> </hibernate-mapping> Help me please. Where I’m wrong?

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  • Google App Engine JDO how to define class fields ?

    - by Frank
    I have a class like this : import java.io.*; import java.util.*; public class Contact_Info_Entry implements Serializable { public static final long serialVersionUID=26362862L; String Contact_Id,First_Name="",Last_Name="",Company_Name="",Branch_Name="",Address_1="",Address_2="",City="",State="",Zip="",Country="",E_Mail="",Phone; int I_1,I_2; float F_1,F_2; boolean B_1,B_2; GregorianCalendar Date_1, Date_2; Vector<String> A_Vector=new Vector<String>(); public Contact_Info_Entry() { } ...... } If I want to translate it to a class for JDO, do I need to define each field by it self or can I do a group at a time ? For instance do I have to make it like this : @PersistenceCapable(identityType=IdentityType.APPLICATION) public class Contact_Info_Entry implements Serializable { @PrimaryKey @Persistent(valueStrategy=IdGeneratorStrategy.IDENTITY) private Long id; @Persistent public static final long serialVersionUID=26362862L; @Persistent String Contact_Id; @Persistent String First_Name; @Persistent String Last_Name; ...... @Persistent int I_1; @Persistent int I_2; ... @Persistent float F_1; ... @Persistent boolean B_1; @Persistent boolean B_2; @Persistent GregorianCalendar Date_1; ... @Persistent Vector<String> A_Vector=new Vector<String>(); public Contact_Info_Entry() { } ...... } Or can I do a group at a time like this : @PersistenceCapable(identityType=IdentityType.APPLICATION) public class Contact_Info_Entry implements Serializable { @PrimaryKey @Persistent(valueStrategy=IdGeneratorStrategy.IDENTITY) private Long id; @Persistent public static final long serialVersionUID=26362862L; @Persistent String Contact_Id,First_Name,Last_Name=""; ...... @Persistent int I_1=0,I_2=1; ... @Persistent float F_1; ... @Persistent boolean B_1,B_2; @Persistent GregorianCalendar Date_1; ... @Persistent Vector<String> A_Vector=new Vector<String>(); public Contact_Info_Entry() { } ...... } Or can I skip the "@Persistent" all together like this : import java.io.*; import java.util.*; @PersistenceCapable(identityType=IdentityType.APPLICATION) public class Contact_Info_Entry implements Serializable { public static final long serialVersionUID=26362862L; String Contact_Id,First_Name="",Last_Name="",Company_Name="",Branch_Name="",Address_1="",Address_2="",City="",State="",Zip="",Country="", E_Mail="",Phone; int I_1,I_2; float F_1,F_2; boolean B_1,B_2; GregorianCalendar Date_1, Date_2; Vector<String> A_Vector=new Vector<String>(); public Contact_Info_Entry() { } ...... } Which are correct ? Frank

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  • Google App Engine JDO how to define instance fields ?

    - by Frank
    I have a class like this : import java.io.*; import java.util.*; public class Contact_Info_Entry implements Serializable { public static final long serialVersionUID=26362862L; String Contact_Id,First_Name="",Last_Name="",Company_Name="",Branch_Name="",Address_1="",Address_2="",City="",State="",Zip="",Country="",E_Mail="",Phone; int I_1,I_2; float F_1,F_2; boolean B_1,B_2; GregorianCalendar Date_1, Date_2; Vector<String> A_Vector=new Vector<String>(); public Contact_Info_Entry() { } ...... } If I want to translate it to a class for JDO, do I need to define each field by it self or can I do a group at a time ? For instance do I have to make it like this : @PersistenceCapable(identityType=IdentityType.APPLICATION) public class Contact_Info_Entry implements Serializable { @PrimaryKey @Persistent(valueStrategy=IdGeneratorStrategy.IDENTITY) private Long id; @Persistent public static final long serialVersionUID=26362862L; @Persistent String Contact_Id; @Persistent String First_Name; @Persistent String Last_Name; ...... @Persistent int I_1; @Persistent int I_2; ... @Persistent float F_1; ... @Persistent boolean B_1; @Persistent boolean B_2; @Persistent GregorianCalendar Date_1; ... @Persistent Vector<String> A_Vector=new Vector<String>(); public Contact_Info_Entry() { } ...... } Or can I do a group at a time like this : @PersistenceCapable(identityType=IdentityType.APPLICATION) public class Contact_Info_Entry implements Serializable { @PrimaryKey @Persistent(valueStrategy=IdGeneratorStrategy.IDENTITY) private Long id; @Persistent public static final long serialVersionUID=26362862L; @Persistent String Contact_Id,First_Name,Last_Name=""; ...... @Persistent int I_1=0,I_2=1; ... @Persistent float F_1; ... @Persistent boolean B_1,B_2; @Persistent GregorianCalendar Date_1; ... @Persistent Vector<String> A_Vector=new Vector<String>(); public Contact_Info_Entry() { } ...... } Or can I skip the "@Persistent" all together like this : import java.io.*; import java.util.*; @PersistenceCapable(identityType=IdentityType.APPLICATION) public class Contact_Info_Entry implements Serializable { public static final long serialVersionUID=26362862L; String Contact_Id,First_Name="",Last_Name="",Company_Name="",Branch_Name="",Address_1="",Address_2="",City="",State="",Zip="",Country="", E_Mail="",Phone; int I_1,I_2; float F_1,F_2; boolean B_1,B_2; GregorianCalendar Date_1, Date_2; Vector<String> A_Vector=new Vector<String>(); public Contact_Info_Entry() { } ...... } Which are correct ? Frank

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  • GWT with JDO problem

    - by Maksim
    I just start playing with GWT I'm having a really hard time to make GWT + JAVA + JDO + Google AppEngine working with DataStore. I was trying to follow different tutorial but had no luck. For example I wend to these tutorials: TUT1 TUT2 I was not able to figure out how and what i need to do in order to make this work. Please look at my simple code and tell me what do i need to do so i can persist it to the datastore: 1. ADDRESS ENTITY package com.example.rpccalls.client; import java.io.Serializable; import javax.jdo.annotations.IdGeneratorStrategy; import javax.jdo.annotations.Persistent; import javax.jdo.annotations.PrimaryKey; public class Address implements Serializable{ @PrimaryKey @Persistent(valueStrategy = IdGeneratorStrategy.IDENTITY) private int addressID; @Persistent private String address1; @Persistent private String address2; @Persistent private String city; @Persistent private String state; @Persistent private String zip; public Address(){} public Address(String a1, String a2, String city, String state, String zip){ this.address1 = a1; this.address2 = a2; this.city = city; this.state = state; this.zip = zip; } /* Setters and Getters */ } 2. PERSON ENTITY package com.example.rpccalls.client; import java.io.Serializable; import java.util.ArrayList; import javax.jdo.annotations.IdGeneratorStrategy; import javax.jdo.annotations.PersistenceCapable; import javax.jdo.annotations.Persistent; import javax.jdo.annotations.PrimaryKey; import com.google.appengine.api.datastore.Key; @PersistenceCapable public class Person implements Serializable{ @PrimaryKey @Persistent(valueStrategy = IdGeneratorStrategy.IDENTITY) private Key key; @Persistent private String name; @Persistent private int age; @Persistent private char gender; @Persistent ArrayList<Address> addresses; public Person(){} public Person(String name, int age, char gender){ this.name = name; this.age = age; this.gender = gender; } /* Getters and Setters */ } 3. RPCCalls package com.example.rpccalls.client; import java.util.ArrayList; import com.google.gwt.core.client.EntryPoint; import com.google.gwt.core.client.GWT; import com.google.gwt.event.dom.client.ClickEvent; import com.google.gwt.event.dom.client.ClickHandler; import com.google.gwt.user.client.Window; import com.google.gwt.user.client.rpc.AsyncCallback; import com.google.gwt.user.client.ui.Button; import com.google.gwt.user.client.ui.RootPanel; import com.google.gwt.user.client.ui.TextBox; public class RPCCalls implements EntryPoint { private static final String SERVER_ERROR = "An error occurred while attempting to contact the server. Please check your network connection and try again."; private final RPCCallsServiceAsync rpccallService = GWT.create(RPCCallsService.class); TextBox nameTxt = new TextBox(); Button btnSave = getBtnSave(); public void onModuleLoad() { RootPanel.get("inputName").add(nameTxt); RootPanel.get("btnSave").add(btnSave); } private Button getBtnSave(){ Button btnSave = new Button("SAVE"); btnSave.addClickHandler( new ClickHandler(){ public void onClick(ClickEvent event){ saveData2DB(nameTxt.getText()); } } ); return btnSave; } void saveData2DB(String name){ AsyncCallback<String> callback = new AsyncCallback<String>() { public void onFailure(Throwable caught) { Window.alert("WOOOHOOO, ERROR: " + SERVER_ERROR);

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  • Is it a missing implementation with JPA implementation of hibernate??

    - by Jegan
    Hi all, On my way in understanding the transaction-type attribute of persistence.xml, i came across an issue / discrepency between hibernate-core and JPA-hibernate which looks weird. I am not pretty sure whether it is a missing implementation with JPA of hibernate. Let me post the comparison between the outcome of JPA implementation and the hibernate implementation of the same concept. Environment Eclipse 3.5.1 JSE v1.6.0_05 Hibernate v3.2.3 [for hibernate core] Hibernate-EntityManger v3.4.0 [for JPA] MySQL DB v5.0 Issue 1.Hibernate core package com.expt.hibernate.core; import java.io.Serializable; public final class Student implements Serializable { private int studId; private String studName; private String studEmailId; public Student(final String studName, final String studEmailId) { this.studName = studName; this.studEmailId = studEmailId; } public int getStudId() { return this.studId; } public String getStudName() { return this.studName; } public String getStudEmailId() { return this.studEmailId; } private void setStudId(int studId) { this.studId = studId; } private void setStudName(String studName) { this.studName = stuName; } private void setStudEmailId(int studEmailId) { this.studEmailId = studEmailId; } } 2. JPA implementaion of Hibernate package com.expt.hibernate.jpa; import java.io.Serializable; import javax.persistence.Column; import javax.persistence.Entity; import javax.persistence.GeneratedValue; import javax.persistence.Id; import javax.persistence.Table; @Entity @Table(name = "Student_Info") public final class Student implements Serializable { @Id @GeneratedValue @Column(name = "STUD_ID", length = 5) private int studId; @Column(name = "STUD_NAME", nullable = false, length = 25) private String studName; @Column(name = "STUD_EMAIL", nullable = true, length = 30) private String studEmailId; public Student(final String studName, final String studEmailId) { this.studName = studName; this.studEmailId = studEmailId; } public int getStudId() { return this.studId; } public String getStudName() { return this.studName; } public String getStudEmailId() { return this.studEmailId; } } Also, I have provided the DB configuration properties in the associated hibernate-cfg.xml [in case of hibernate core] and persistence.xml [in case of JPA (hibernate entity manager)]. create a driver and perform add a student and query for the list of students and print their details. Then the issue comes when you run the driver program. Hibernate core - output Exception in thread "main" org.hibernate.InstantiationException: No default constructor for entity: com.expt.hibernate.core.Student at org.hibernate.tuple.PojoInstantiator.instantiate(PojoInstantiator.java:84) at org.hibernate.tuple.PojoInstantiator.instantiate(PojoInstantiator.java:100) at org.hibernate.tuple.entity.AbstractEntityTuplizer.instantiate(AbstractEntityTuplizer.java:351) at org.hibernate.persister.entity.AbstractEntityPersister.instantiate(AbstractEntityPersister.java:3604) .... .... This exception is flashed when the driver is executed for the first time itself. JPA Hibernate - output First execution of the driver on a fresh DB provided the following output. DEBUG SQL:111 - insert into student.Student_Info (STUD_EMAIL, STUD_NAME) values (?, ?) 17:38:24,229 DEBUG SQL:111 - select student0_.STUD_ID as STUD1_0_, student0_.STUD_EMAIL as STUD2_0_, student0_.STUD_NAME as STUD3_0_ from student.Student_Info student0_ student list size == 1 1 || Jegan || [email protected] second execution of the driver provided the following output. DEBUG SQL:111 - insert into student.Student_Info (STUD_EMAIL, STUD_NAME) values (?, ?) 17:40:25,254 DEBUG SQL:111 - select student0_.STUD_ID as STUD1_0_, student0_.STUD_EMAIL as STUD2_0_, student0_.STUD_NAME as STUD3_0_ from student.Student_Info student0_ Exception in thread "main" javax.persistence.PersistenceException: org.hibernate.InstantiationException: No default constructor for entity: com.expt.hibernate.jpa.Student at org.hibernate.ejb.AbstractEntityManagerImpl.throwPersistenceException(AbstractEntityManagerImpl.java:614) at org.hibernate.ejb.QueryImpl.getResultList(QueryImpl.java:76) at driver.StudentDriver.main(StudentDriver.java:43) Caused by: org.hibernate.InstantiationException: No default constructor for entity: com.expt.hibernate.jpa.Student .... .... Could anyone please let me know if you have encountered this sort of inconsistency? Also, could anyone please let me know if the issue is a missing implementation with JPA-Hibernate? ~ Jegan

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  • value types in the vm

    - by john.rose
    value types in the vm p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times} p.p2 {margin: 0.0px 0.0px 14.0px 0.0px; font: 14.0px Times} p.p3 {margin: 0.0px 0.0px 12.0px 0.0px; font: 14.0px Times} p.p4 {margin: 0.0px 0.0px 15.0px 0.0px; font: 14.0px Times} p.p5 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Courier} p.p6 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Courier; min-height: 17.0px} p.p7 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times; min-height: 18.0px} p.p8 {margin: 0.0px 0.0px 0.0px 36.0px; text-indent: -36.0px; font: 14.0px Times; min-height: 18.0px} p.p9 {margin: 0.0px 0.0px 12.0px 0.0px; font: 14.0px Times; min-height: 18.0px} p.p10 {margin: 0.0px 0.0px 12.0px 0.0px; font: 14.0px Times; color: #000000} li.li1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times} li.li7 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times; min-height: 18.0px} span.s1 {font: 14.0px Courier} span.s2 {color: #000000} span.s3 {font: 14.0px Courier; color: #000000} ol.ol1 {list-style-type: decimal} Or, enduring values for a changing world. Introduction A value type is a data type which, generally speaking, is designed for being passed by value in and out of methods, and stored by value in data structures. The only value types which the Java language directly supports are the eight primitive types. Java indirectly and approximately supports value types, if they are implemented in terms of classes. For example, both Integer and String may be viewed as value types, especially if their usage is restricted to avoid operations appropriate to Object. In this note, we propose a definition of value types in terms of a design pattern for Java classes, accompanied by a set of usage restrictions. We also sketch the relation of such value types to tuple types (which are a JVM-level notion), and point out JVM optimizations that can apply to value types. This note is a thought experiment to extend the JVM’s performance model in support of value types. The demonstration has two phases.  Initially the extension can simply use design patterns, within the current bytecode architecture, and in today’s Java language. But if the performance model is to be realized in practice, it will probably require new JVM bytecode features, changes to the Java language, or both.  We will look at a few possibilities for these new features. An Axiom of Value In the context of the JVM, a value type is a data type equipped with construction, assignment, and equality operations, and a set of typed components, such that, whenever two variables of the value type produce equal corresponding values for their components, the values of the two variables cannot be distinguished by any JVM operation. Here are some corollaries: A value type is immutable, since otherwise a copy could be constructed and the original could be modified in one of its components, allowing the copies to be distinguished. Changing the component of a value type requires construction of a new value. The equals and hashCode operations are strictly component-wise. If a value type is represented by a JVM reference, that reference cannot be successfully synchronized on, and cannot be usefully compared for reference equality. A value type can be viewed in terms of what it doesn’t do. We can say that a value type omits all value-unsafe operations, which could violate the constraints on value types.  These operations, which are ordinarily allowed for Java object types, are pointer equality comparison (the acmp instruction), synchronization (the monitor instructions), all the wait and notify methods of class Object, and non-trivial finalize methods. The clone method is also value-unsafe, although for value types it could be treated as the identity function. Finally, and most importantly, any side effect on an object (however visible) also counts as an value-unsafe operation. A value type may have methods, but such methods must not change the components of the value. It is reasonable and useful to define methods like toString, equals, and hashCode on value types, and also methods which are specifically valuable to users of the value type. Representations of Value Value types have two natural representations in the JVM, unboxed and boxed. An unboxed value consists of the components, as simple variables. For example, the complex number x=(1+2i), in rectangular coordinate form, may be represented in unboxed form by the following pair of variables: /*Complex x = Complex.valueOf(1.0, 2.0):*/ double x_re = 1.0, x_im = 2.0; These variables might be locals, parameters, or fields. Their association as components of a single value is not defined to the JVM. Here is a sample computation which computes the norm of the difference between two complex numbers: double distance(/*Complex x:*/ double x_re, double x_im,         /*Complex y:*/ double y_re, double y_im) {     /*Complex z = x.minus(y):*/     double z_re = x_re - y_re, z_im = x_im - y_im;     /*return z.abs():*/     return Math.sqrt(z_re*z_re + z_im*z_im); } A boxed representation groups component values under a single object reference. The reference is to a ‘wrapper class’ that carries the component values in its fields. (A primitive type can naturally be equated with a trivial value type with just one component of that type. In that view, the wrapper class Integer can serve as a boxed representation of value type int.) The unboxed representation of complex numbers is practical for many uses, but it fails to cover several major use cases: return values, array elements, and generic APIs. The two components of a complex number cannot be directly returned from a Java function, since Java does not support multiple return values. The same story applies to array elements: Java has no ’array of structs’ feature. (Double-length arrays are a possible workaround for complex numbers, but not for value types with heterogeneous components.) By generic APIs I mean both those which use generic types, like Arrays.asList and those which have special case support for primitive types, like String.valueOf and PrintStream.println. Those APIs do not support unboxed values, and offer some problems to boxed values. Any ’real’ JVM type should have a story for returns, arrays, and API interoperability. The basic problem here is that value types fall between primitive types and object types. Value types are clearly more complex than primitive types, and object types are slightly too complicated. Objects are a little bit dangerous to use as value carriers, since object references can be compared for pointer equality, and can be synchronized on. Also, as many Java programmers have observed, there is often a performance cost to using wrapper objects, even on modern JVMs. Even so, wrapper classes are a good starting point for talking about value types. If there were a set of structural rules and restrictions which would prevent value-unsafe operations on value types, wrapper classes would provide a good notation for defining value types. This note attempts to define such rules and restrictions. Let’s Start Coding Now it is time to look at some real code. Here is a definition, written in Java, of a complex number value type. @ValueSafe public final class Complex implements java.io.Serializable {     // immutable component structure:     public final double re, im;     private Complex(double re, double im) {         this.re = re; this.im = im;     }     // interoperability methods:     public String toString() { return "Complex("+re+","+im+")"; }     public List<Double> asList() { return Arrays.asList(re, im); }     public boolean equals(Complex c) {         return re == c.re && im == c.im;     }     public boolean equals(@ValueSafe Object x) {         return x instanceof Complex && equals((Complex) x);     }     public int hashCode() {         return 31*Double.valueOf(re).hashCode()                 + Double.valueOf(im).hashCode();     }     // factory methods:     public static Complex valueOf(double re, double im) {         return new Complex(re, im);     }     public Complex changeRe(double re2) { return valueOf(re2, im); }     public Complex changeIm(double im2) { return valueOf(re, im2); }     public static Complex cast(@ValueSafe Object x) {         return x == null ? ZERO : (Complex) x;     }     // utility methods and constants:     public Complex plus(Complex c)  { return new Complex(re+c.re, im+c.im); }     public Complex minus(Complex c) { return new Complex(re-c.re, im-c.im); }     public double abs() { return Math.sqrt(re*re + im*im); }     public static final Complex PI = valueOf(Math.PI, 0.0);     public static final Complex ZERO = valueOf(0.0, 0.0); } This is not a minimal definition, because it includes some utility methods and other optional parts.  The essential elements are as follows: The class is marked as a value type with an annotation. The class is final, because it does not make sense to create subclasses of value types. The fields of the class are all non-private and final.  (I.e., the type is immutable and structurally transparent.) From the supertype Object, all public non-final methods are overridden. The constructor is private. Beyond these bare essentials, we can observe the following features in this example, which are likely to be typical of all value types: One or more factory methods are responsible for value creation, including a component-wise valueOf method. There are utility methods for complex arithmetic and instance creation, such as plus and changeIm. There are static utility constants, such as PI. The type is serializable, using the default mechanisms. There are methods for converting to and from dynamically typed references, such as asList and cast. The Rules In order to use value types properly, the programmer must avoid value-unsafe operations.  A helpful Java compiler should issue errors (or at least warnings) for code which provably applies value-unsafe operations, and should issue warnings for code which might be correct but does not provably avoid value-unsafe operations.  No such compilers exist today, but to simplify our account here, we will pretend that they do exist. A value-safe type is any class, interface, or type parameter marked with the @ValueSafe annotation, or any subtype of a value-safe type.  If a value-safe class is marked final, it is in fact a value type.  All other value-safe classes must be abstract.  The non-static fields of a value class must be non-public and final, and all its constructors must be private. Under the above rules, a standard interface could be helpful to define value types like Complex.  Here is an example: @ValueSafe public interface ValueType extends java.io.Serializable {     // All methods listed here must get redefined.     // Definitions must be value-safe, which means     // they may depend on component values only.     List<? extends Object> asList();     int hashCode();     boolean equals(@ValueSafe Object c);     String toString(); } //@ValueSafe inherited from supertype: public final class Complex implements ValueType { … The main advantage of such a conventional interface is that (unlike an annotation) it is reified in the runtime type system.  It could appear as an element type or parameter bound, for facilities which are designed to work on value types only.  More broadly, it might assist the JVM to perform dynamic enforcement of the rules for value types. Besides types, the annotation @ValueSafe can mark fields, parameters, local variables, and methods.  (This is redundant when the type is also value-safe, but may be useful when the type is Object or another supertype of a value type.)  Working forward from these annotations, an expression E is defined as value-safe if it satisfies one or more of the following: The type of E is a value-safe type. E names a field, parameter, or local variable whose declaration is marked @ValueSafe. E is a call to a method whose declaration is marked @ValueSafe. E is an assignment to a value-safe variable, field reference, or array reference. E is a cast to a value-safe type from a value-safe expression. E is a conditional expression E0 ? E1 : E2, and both E1 and E2 are value-safe. Assignments to value-safe expressions and initializations of value-safe names must take their values from value-safe expressions. A value-safe expression may not be the subject of a value-unsafe operation.  In particular, it cannot be synchronized on, nor can it be compared with the “==” operator, not even with a null or with another value-safe type. In a program where all of these rules are followed, no value-type value will be subject to a value-unsafe operation.  Thus, the prime axiom of value types will be satisfied, that no two value type will be distinguishable as long as their component values are equal. More Code To illustrate these rules, here are some usage examples for Complex: Complex pi = Complex.valueOf(Math.PI, 0); Complex zero = pi.changeRe(0);  //zero = pi; zero.re = 0; ValueType vtype = pi; @SuppressWarnings("value-unsafe")   Object obj = pi; @ValueSafe Object obj2 = pi; obj2 = new Object();  // ok List<Complex> clist = new ArrayList<Complex>(); clist.add(pi);  // (ok assuming List.add param is @ValueSafe) List<ValueType> vlist = new ArrayList<ValueType>(); vlist.add(pi);  // (ok) List<Object> olist = new ArrayList<Object>(); olist.add(pi);  // warning: "value-unsafe" boolean z = pi.equals(zero); boolean z1 = (pi == zero);  // error: reference comparison on value type boolean z2 = (pi == null);  // error: reference comparison on value type boolean z3 = (pi == obj2);  // error: reference comparison on value type synchronized (pi) { }  // error: synch of value, unpredictable result synchronized (obj2) { }  // unpredictable result Complex qq = pi; qq = null;  // possible NPE; warning: “null-unsafe" qq = (Complex) obj;  // warning: “null-unsafe" qq = Complex.cast(obj);  // OK @SuppressWarnings("null-unsafe")   Complex empty = null;  // possible NPE qq = empty;  // possible NPE (null pollution) The Payoffs It follows from this that either the JVM or the java compiler can replace boxed value-type values with unboxed ones, without affecting normal computations.  Fields and variables of value types can be split into their unboxed components.  Non-static methods on value types can be transformed into static methods which take the components as value parameters. Some common questions arise around this point in any discussion of value types. Why burden the programmer with all these extra rules?  Why not detect programs automagically and perform unboxing transparently?  The answer is that it is easy to break the rules accidently unless they are agreed to by the programmer and enforced.  Automatic unboxing optimizations are tantalizing but (so far) unreachable ideal.  In the current state of the art, it is possible exhibit benchmarks in which automatic unboxing provides the desired effects, but it is not possible to provide a JVM with a performance model that assures the programmer when unboxing will occur.  This is why I’m writing this note, to enlist help from, and provide assurances to, the programmer.  Basically, I’m shooting for a good set of user-supplied “pragmas” to frame the desired optimization. Again, the important thing is that the unboxing must be done reliably, or else programmers will have no reason to work with the extra complexity of the value-safety rules.  There must be a reasonably stable performance model, wherein using a value type has approximately the same performance characteristics as writing the unboxed components as separate Java variables. There are some rough corners to the present scheme.  Since Java fields and array elements are initialized to null, value-type computations which incorporate uninitialized variables can produce null pointer exceptions.  One workaround for this is to require such variables to be null-tested, and the result replaced with a suitable all-zero value of the value type.  That is what the “cast” method does above. Generically typed APIs like List<T> will continue to manipulate boxed values always, at least until we figure out how to do reification of generic type instances.  Use of such APIs will elicit warnings until their type parameters (and/or relevant members) are annotated or typed as value-safe.  Retrofitting List<T> is likely to expose flaws in the present scheme, which we will need to engineer around.  Here are a couple of first approaches: public interface java.util.List<@ValueSafe T> extends Collection<T> { … public interface java.util.List<T extends Object|ValueType> extends Collection<T> { … (The second approach would require disjunctive types, in which value-safety is “contagious” from the constituent types.) With more transformations, the return value types of methods can also be unboxed.  This may require significant bytecode-level transformations, and would work best in the presence of a bytecode representation for multiple value groups, which I have proposed elsewhere under the title “Tuples in the VM”. But for starters, the JVM can apply this transformation under the covers, to internally compiled methods.  This would give a way to express multiple return values and structured return values, which is a significant pain-point for Java programmers, especially those who work with low-level structure types favored by modern vector and graphics processors.  The lack of multiple return values has a strong distorting effect on many Java APIs. Even if the JVM fails to unbox a value, there is still potential benefit to the value type.  Clustered computing systems something have copy operations (serialization or something similar) which apply implicitly to command operands.  When copying JVM objects, it is extremely helpful to know when an object’s identity is important or not.  If an object reference is a copied operand, the system may have to create a proxy handle which points back to the original object, so that side effects are visible.  Proxies must be managed carefully, and this can be expensive.  On the other hand, value types are exactly those types which a JVM can “copy and forget” with no downside. Array types are crucial to bulk data interfaces.  (As data sizes and rates increase, bulk data becomes more important than scalar data, so arrays are definitely accompanying us into the future of computing.)  Value types are very helpful for adding structure to bulk data, so a successful value type mechanism will make it easier for us to express richer forms of bulk data. Unboxing arrays (i.e., arrays containing unboxed values) will provide better cache and memory density, and more direct data movement within clustered or heterogeneous computing systems.  They require the deepest transformations, relative to today’s JVM.  There is an impedance mismatch between value-type arrays and Java’s covariant array typing, so compromises will need to be struck with existing Java semantics.  It is probably worth the effort, since arrays of unboxed value types are inherently more memory-efficient than standard Java arrays, which rely on dependent pointer chains. It may be sufficient to extend the “value-safe” concept to array declarations, and allow low-level transformations to change value-safe array declarations from the standard boxed form into an unboxed tuple-based form.  Such value-safe arrays would not be convertible to Object[] arrays.  Certain connection points, such as Arrays.copyOf and System.arraycopy might need additional input/output combinations, to allow smooth conversion between arrays with boxed and unboxed elements. Alternatively, the correct solution may have to wait until we have enough reification of generic types, and enough operator overloading, to enable an overhaul of Java arrays. Implicit Method Definitions The example of class Complex above may be unattractively complex.  I believe most or all of the elements of the example class are required by the logic of value types. If this is true, a programmer who writes a value type will have to write lots of error-prone boilerplate code.  On the other hand, I think nearly all of the code (except for the domain-specific parts like plus and minus) can be implicitly generated. Java has a rule for implicitly defining a class’s constructor, if no it defines no constructors explicitly.  Likewise, there are rules for providing default access modifiers for interface members.  Because of the highly regular structure of value types, it might be reasonable to perform similar implicit transformations on value types.  Here’s an example of a “highly implicit” definition of a complex number type: public class Complex implements ValueType {  // implicitly final     public double re, im;  // implicitly public final     //implicit methods are defined elementwise from te fields:     //  toString, asList, equals(2), hashCode, valueOf, cast     //optionally, explicit methods (plus, abs, etc.) would go here } In other words, with the right defaults, a simple value type definition can be a one-liner.  The observant reader will have noticed the similarities (and suitable differences) between the explicit methods above and the corresponding methods for List<T>. Another way to abbreviate such a class would be to make an annotation the primary trigger of the functionality, and to add the interface(s) implicitly: public @ValueType class Complex { … // implicitly final, implements ValueType (But to me it seems better to communicate the “magic” via an interface, even if it is rooted in an annotation.) Implicitly Defined Value Types So far we have been working with nominal value types, which is to say that the sequence of typed components is associated with a name and additional methods that convey the intention of the programmer.  A simple ordered pair of floating point numbers can be variously interpreted as (to name a few possibilities) a rectangular or polar complex number or Cartesian point.  The name and the methods convey the intended meaning. But what if we need a truly simple ordered pair of floating point numbers, without any further conceptual baggage?  Perhaps we are writing a method (like “divideAndRemainder”) which naturally returns a pair of numbers instead of a single number.  Wrapping the pair of numbers in a nominal type (like “QuotientAndRemainder”) makes as little sense as wrapping a single return value in a nominal type (like “Quotient”).  What we need here are structural value types commonly known as tuples. For the present discussion, let us assign a conventional, JVM-friendly name to tuples, roughly as follows: public class java.lang.tuple.$DD extends java.lang.tuple.Tuple {      double $1, $2; } Here the component names are fixed and all the required methods are defined implicitly.  The supertype is an abstract class which has suitable shared declarations.  The name itself mentions a JVM-style method parameter descriptor, which may be “cracked” to determine the number and types of the component fields. The odd thing about such a tuple type (and structural types in general) is it must be instantiated lazily, in response to linkage requests from one or more classes that need it.  The JVM and/or its class loaders must be prepared to spin a tuple type on demand, given a simple name reference, $xyz, where the xyz is cracked into a series of component types.  (Specifics of naming and name mangling need some tasteful engineering.) Tuples also seem to demand, even more than nominal types, some support from the language.  (This is probably because notations for non-nominal types work best as combinations of punctuation and type names, rather than named constructors like Function3 or Tuple2.)  At a minimum, languages with tuples usually (I think) have some sort of simple bracket notation for creating tuples, and a corresponding pattern-matching syntax (or “destructuring bind”) for taking tuples apart, at least when they are parameter lists.  Designing such a syntax is no simple thing, because it ought to play well with nominal value types, and also with pre-existing Java features, such as method parameter lists, implicit conversions, generic types, and reflection.  That is a task for another day. Other Use Cases Besides complex numbers and simple tuples there are many use cases for value types.  Many tuple-like types have natural value-type representations. These include rational numbers, point locations and pixel colors, and various kinds of dates and addresses. Other types have a variable-length ‘tail’ of internal values. The most common example of this is String, which is (mathematically) a sequence of UTF-16 character values. Similarly, bit vectors, multiple-precision numbers, and polynomials are composed of sequences of values. Such types include, in their representation, a reference to a variable-sized data structure (often an array) which (somehow) represents the sequence of values. The value type may also include ’header’ information. Variable-sized values often have a length distribution which favors short lengths. In that case, the design of the value type can make the first few values in the sequence be direct ’header’ fields of the value type. In the common case where the header is enough to represent the whole value, the tail can be a shared null value, or even just a null reference. Note that the tail need not be an immutable object, as long as the header type encapsulates it well enough. This is the case with String, where the tail is a mutable (but never mutated) character array. Field types and their order must be a globally visible part of the API.  The structure of the value type must be transparent enough to have a globally consistent unboxed representation, so that all callers and callees agree about the type and order of components  that appear as parameters, return types, and array elements.  This is a trade-off between efficiency and encapsulation, which is forced on us when we remove an indirection enjoyed by boxed representations.  A JVM-only transformation would not care about such visibility, but a bytecode transformation would need to take care that (say) the components of complex numbers would not get swapped after a redefinition of Complex and a partial recompile.  Perhaps constant pool references to value types need to declare the field order as assumed by each API user. This brings up the delicate status of private fields in a value type.  It must always be possible to load, store, and copy value types as coordinated groups, and the JVM performs those movements by moving individual scalar values between locals and stack.  If a component field is not public, what is to prevent hostile code from plucking it out of the tuple using a rogue aload or astore instruction?  Nothing but the verifier, so we may need to give it more smarts, so that it treats value types as inseparable groups of stack slots or locals (something like long or double). My initial thought was to make the fields always public, which would make the security problem moot.  But public is not always the right answer; consider the case of String, where the underlying mutable character array must be encapsulated to prevent security holes.  I believe we can win back both sides of the tradeoff, by training the verifier never to split up the components in an unboxed value.  Just as the verifier encapsulates the two halves of a 64-bit primitive, it can encapsulate the the header and body of an unboxed String, so that no code other than that of class String itself can take apart the values. Similar to String, we could build an efficient multi-precision decimal type along these lines: public final class DecimalValue extends ValueType {     protected final long header;     protected private final BigInteger digits;     public DecimalValue valueOf(int value, int scale) {         assert(scale >= 0);         return new DecimalValue(((long)value << 32) + scale, null);     }     public DecimalValue valueOf(long value, int scale) {         if (value == (int) value)             return valueOf((int)value, scale);         return new DecimalValue(-scale, new BigInteger(value));     } } Values of this type would be passed between methods as two machine words. Small values (those with a significand which fits into 32 bits) would be represented without any heap data at all, unless the DecimalValue itself were boxed. (Note the tension between encapsulation and unboxing in this case.  It would be better if the header and digits fields were private, but depending on where the unboxing information must “leak”, it is probably safer to make a public revelation of the internal structure.) Note that, although an array of Complex can be faked with a double-length array of double, there is no easy way to fake an array of unboxed DecimalValues.  (Either an array of boxed values or a transposed pair of homogeneous arrays would be reasonable fallbacks, in a current JVM.)  Getting the full benefit of unboxing and arrays will require some new JVM magic. Although the JVM emphasizes portability, system dependent code will benefit from using machine-level types larger than 64 bits.  For example, the back end of a linear algebra package might benefit from value types like Float4 which map to stock vector types.  This is probably only worthwhile if the unboxing arrays can be packed with such values. More Daydreams A more finely-divided design for dynamic enforcement of value safety could feature separate marker interfaces for each invariant.  An empty marker interface Unsynchronizable could cause suitable exceptions for monitor instructions on objects in marked classes.  More radically, a Interchangeable marker interface could cause JVM primitives that are sensitive to object identity to raise exceptions; the strangest result would be that the acmp instruction would have to be specified as raising an exception. @ValueSafe public interface ValueType extends java.io.Serializable,         Unsynchronizable, Interchangeable { … public class Complex implements ValueType {     // inherits Serializable, Unsynchronizable, Interchangeable, @ValueSafe     … It seems possible that Integer and the other wrapper types could be retro-fitted as value-safe types.  This is a major change, since wrapper objects would be unsynchronizable and their references interchangeable.  It is likely that code which violates value-safety for wrapper types exists but is uncommon.  It is less plausible to retro-fit String, since the prominent operation String.intern is often used with value-unsafe code. We should also reconsider the distinction between boxed and unboxed values in code.  The design presented above obscures that distinction.  As another thought experiment, we could imagine making a first class distinction in the type system between boxed and unboxed representations.  Since only primitive types are named with a lower-case initial letter, we could define that the capitalized version of a value type name always refers to the boxed representation, while the initial lower-case variant always refers to boxed.  For example: complex pi = complex.valueOf(Math.PI, 0); Complex boxPi = pi;  // convert to boxed myList.add(boxPi); complex z = myList.get(0);  // unbox Such a convention could perhaps absorb the current difference between int and Integer, double and Double. It might also allow the programmer to express a helpful distinction among array types. As said above, array types are crucial to bulk data interfaces, but are limited in the JVM.  Extending arrays beyond the present limitations is worth thinking about; for example, the Maxine JVM implementation has a hybrid object/array type.  Something like this which can also accommodate value type components seems worthwhile.  On the other hand, does it make sense for value types to contain short arrays?  And why should random-access arrays be the end of our design process, when bulk data is often sequentially accessed, and it might make sense to have heterogeneous streams of data as the natural “jumbo” data structure.  These considerations must wait for another day and another note. More Work It seems to me that a good sequence for introducing such value types would be as follows: Add the value-safety restrictions to an experimental version of javac. Code some sample applications with value types, including Complex and DecimalValue. Create an experimental JVM which internally unboxes value types but does not require new bytecodes to do so.  Ensure the feasibility of the performance model for the sample applications. Add tuple-like bytecodes (with or without generic type reification) to a major revision of the JVM, and teach the Java compiler to switch in the new bytecodes without code changes. A staggered roll-out like this would decouple language changes from bytecode changes, which is always a convenient thing. A similar investigation should be applied (concurrently) to array types.  In this case, it seems to me that the starting point is in the JVM: Add an experimental unboxing array data structure to a production JVM, perhaps along the lines of Maxine hybrids.  No bytecode or language support is required at first; everything can be done with encapsulated unsafe operations and/or method handles. Create an experimental JVM which internally unboxes value types but does not require new bytecodes to do so.  Ensure the feasibility of the performance model for the sample applications. Add tuple-like bytecodes (with or without generic type reification) to a major revision of the JVM, and teach the Java compiler to switch in the new bytecodes without code changes. That’s enough musing me for now.  Back to work!

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  • .NET Security Part 4

    - by Simon Cooper
    Finally, in this series, I am going to cover some of the security issues that can trip you up when using sandboxed appdomains. DISCLAIMER: I am not a security expert, and this is by no means an exhaustive list. If you actually are writing security-critical code, then get a proper security audit of your code by a professional. The examples below are just illustrations of the sort of things that can go wrong. 1. AppDomainSetup.ApplicationBase The most obvious one is the issue covered in the MSDN documentation on creating a sandbox, in step 3 – the sandboxed appdomain has the same ApplicationBase as the controlling appdomain. So let’s explore what happens when they are the same, and an exception is thrown. In the sandboxed assembly, Sandboxed.dll (IPlugin is an interface in a partially-trusted assembly, with a single MethodToDoThings on it): public class UntrustedPlugin : MarshalByRefObject, IPlugin { // implements IPlugin.MethodToDoThings() public void MethodToDoThings() { throw new EvilException(); } } [Serializable] internal class EvilException : Exception { public override string ToString() { // show we have read access to C:\Windows // read the first 5 directories Console.WriteLine("Pwned! Mwuahahah!"); foreach (var d in Directory.EnumerateDirectories(@"C:\Windows").Take(5)) { Console.WriteLine(d.FullName); } return base.ToString(); } } And in the controlling assembly: // what can possibly go wrong? AppDomainSetup appDomainSetup = new AppDomainSetup { ApplicationBase = AppDomain.CurrentDomain.SetupInformation.ApplicationBase } // only grant permissions to execute // and to read the application base, nothing else PermissionSet restrictedPerms = new PermissionSet(PermissionState.None); restrictedPerms.AddPermission( new SecurityPermission(SecurityPermissionFlag.Execution)); restrictedPerms.AddPermission( new FileIOPermission(FileIOPermissionAccess.Read, appDomainSetup.ApplicationBase); restrictedPerms.AddPermission( new FileIOPermission(FileIOPermissionAccess.pathDiscovery, appDomainSetup.ApplicationBase); // create the sandbox AppDomain sandbox = AppDomain.CreateDomain("Sandbox", null, appDomainSetup, restrictedPerms); // execute UntrustedPlugin in the sandbox // don't crash the application if the sandbox throws an exception IPlugin o = (IPlugin)sandbox.CreateInstanceFromAndUnwrap("Sandboxed.dll", "UntrustedPlugin"); try { o.MethodToDoThings() } catch (Exception e) { Console.WriteLine(e.ToString()); } And the result? Oops. We’ve allowed a class that should be sandboxed to execute code with fully-trusted permissions! How did this happen? Well, the key is the exact meaning of the ApplicationBase property: The application base directory is where the assembly manager begins probing for assemblies. When EvilException is thrown, it propagates from the sandboxed appdomain into the controlling assembly’s appdomain (as it’s marked as Serializable). When the exception is deserialized, the CLR finds and loads the sandboxed dll into the fully-trusted appdomain. Since the controlling appdomain’s ApplicationBase directory contains the sandboxed assembly, the CLR finds and loads the assembly into a full-trust appdomain, and the evil code is executed. So the problem isn’t exactly that the sandboxed appdomain’s ApplicationBase is the same as the controlling appdomain’s, it’s that the sandboxed dll was in such a place that the controlling appdomain could find it as part of the standard assembly resolution mechanism. The sandbox then forced the assembly to load in the controlling appdomain by throwing a serializable exception that propagated outside the sandbox. The easiest fix for this is to keep the sandbox ApplicationBase well away from the ApplicationBase of the controlling appdomain, and don’t allow the sandbox permissions to access the controlling appdomain’s ApplicationBase directory. If you do this, then the sandboxed assembly can’t be accidentally loaded into the fully-trusted appdomain, and the code can’t be executed. If the plugin does try to induce the controlling appdomain to load an assembly it shouldn’t, a SerializationException will be thrown when it tries to load the assembly to deserialize the exception, and no damage will be done. 2. Loading the sandboxed dll into the application appdomain As an extension of the previous point, you shouldn’t directly reference types or methods in the sandboxed dll from your application code. That loads the assembly into the fully-trusted appdomain, and from there code in the assembly could be executed. Instead, pull out methods you want the sandboxed dll to have into an interface or class in a partially-trusted assembly you control, and execute methods via that instead (similar to the example above with the IPlugin interface). If you need to have a look at the assembly before executing it in the sandbox, either examine the assembly using reflection from within the sandbox, or load the assembly into the Reflection-only context in the application’s appdomain. The code in assemblies in the reflection-only context can’t be executed, it can only be reflected upon, thus protecting your appdomain from malicious code. 3. Incorrectly asserting permissions You should only assert permissions when you are absolutely sure they’re safe. For example, this method allows a caller read-access to any file they call this method with, including your documents, any network shares, the C:\Windows directory, etc: [SecuritySafeCritical] public static string GetFileText(string filePath) { new FileIOPermission(FileIOPermissionAccess.Read, filePath).Assert(); return File.ReadAllText(filePath); } Be careful when asserting permissions, and ensure you’re not providing a loophole sandboxed dlls can use to gain access to things they shouldn’t be able to. Conclusion Hopefully, that’s given you an idea of some of the ways it’s possible to get past the .NET security system. As I said before, this post is not exhaustive, and you certainly shouldn’t base any security-critical applications on the contents of this blog post. What this series should help with is understanding the possibilities of the security system, and what all the security attributes and classes mean and what they are used for, if you were to use the security system in the future.

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  • Optimizing a thread safe Java NIO / Serialization / FIFO Queue [migrated]

    - by trialcodr
    I've written a thread safe, persistent FIFO for Serializable items. The reason for reinventing the wheel is that we simply can't afford any third party dependencies in this project and want to keep this really simple. The problem is it isn't fast enough. Most of it is undoubtedly due to reading and writing directly to disk but I think we should be able to squeeze a bit more out of it anyway. Any ideas on how to improve the performance of the 'take'- and 'add'-methods? /** * <code>DiskQueue</code> Persistent, thread safe FIFO queue for * <code>Serializable</code> items. */ public class DiskQueue<ItemT extends Serializable> { public static final int EMPTY_OFFS = -1; public static final int LONG_SIZE = 8; public static final int HEADER_SIZE = LONG_SIZE * 2; private InputStream inputStream; private OutputStream outputStream; private RandomAccessFile file; private FileChannel channel; private long offs = EMPTY_OFFS; private long size = 0; public DiskQueue(String filename) { try { boolean fileExists = new File(filename).exists(); file = new RandomAccessFile(filename, "rwd"); if (fileExists) { size = file.readLong(); offs = file.readLong(); } else { file.writeLong(size); file.writeLong(offs); } } catch (FileNotFoundException e) { throw new RuntimeException(e); } catch (IOException e) { throw new RuntimeException(e); } channel = file.getChannel(); inputStream = Channels.newInputStream(channel); outputStream = Channels.newOutputStream(channel); } /** * Add item to end of queue. */ public void add(ItemT item) { try { synchronized (this) { channel.position(channel.size()); ObjectOutputStream s = new ObjectOutputStream(outputStream); s.writeObject(item); s.flush(); size++; file.seek(0); file.writeLong(size); if (offs == EMPTY_OFFS) { offs = HEADER_SIZE; file.writeLong(offs); } notify(); } } catch (IOException e) { throw new RuntimeException(e); } } /** * Clears overhead by moving the remaining items up and shortening the file. */ public synchronized void defrag() { if (offs > HEADER_SIZE && size > 0) { try { long totalBytes = channel.size() - offs; ByteBuffer buffer = ByteBuffer.allocateDirect((int) totalBytes); channel.position(offs); for (int bytes = 0; bytes < totalBytes;) { int res = channel.read(buffer); if (res == -1) { throw new IOException("Failed to read data into buffer"); } bytes += res; } channel.position(HEADER_SIZE); buffer.flip(); for (int bytes = 0; bytes < totalBytes;) { int res = channel.write(buffer); if (res == -1) { throw new IOException("Failed to write buffer to file"); } bytes += res; } offs = HEADER_SIZE; file.seek(LONG_SIZE); file.writeLong(offs); file.setLength(HEADER_SIZE + totalBytes); } catch (IOException e) { throw new RuntimeException(e); } } } /** * Returns the queue overhead in bytes. */ public synchronized long overhead() { return (offs == EMPTY_OFFS) ? 0 : offs - HEADER_SIZE; } /** * Returns the first item in the queue, blocks if queue is empty. */ public ItemT peek() throws InterruptedException { block(); synchronized (this) { if (offs != EMPTY_OFFS) { return readItem(); } } return peek(); } /** * Returns the number of remaining items in queue. */ public synchronized long size() { return size; } /** * Removes and returns the first item in the queue, blocks if queue is empty. */ public ItemT take() throws InterruptedException { block(); try { synchronized (this) { if (offs != EMPTY_OFFS) { ItemT result = readItem(); size--; offs = channel.position(); file.seek(0); if (offs == channel.size()) { truncate(); } file.writeLong(size); file.writeLong(offs); return result; } } return take(); } catch (IOException e) { throw new RuntimeException(e); } } /** * Throw away all items and reset the file. */ public synchronized void truncate() { try { offs = EMPTY_OFFS; file.setLength(HEADER_SIZE); size = 0; } catch (IOException e) { throw new RuntimeException(e); } } /** * Block until an item is available. */ protected void block() throws InterruptedException { while (offs == EMPTY_OFFS) { try { synchronized (this) { wait(); file.seek(LONG_SIZE); offs = file.readLong(); } } catch (IOException e) { throw new RuntimeException(e); } } } /** * Read and return item. */ @SuppressWarnings("unchecked") protected ItemT readItem() { try { channel.position(offs); return (ItemT) new ObjectInputStream(inputStream).readObject(); } catch (ClassNotFoundException e) { throw new RuntimeException(e); } catch (IOException e) { throw new RuntimeException(e); } } }

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  • DomainService method not compiling; claims "Return types must be an entity ..."

    - by Duncan Bayne
    I have a WCF RIA Domain Service that contains a method I'd like to invoke when the user clicks a button: [Invoke] public MyEntity PerformAnalysis(int someId) { return new MyEntity(); } However, when I try to compile I'm given the following error: Operation named 'PerformAnalysis' does not conform to the required signature. Return types must be an entity, collection of entities, or one of the predefined serializable types. The thing is, as far as I can tell, MyEntity is an entity: [Serializable] public class MyEntity: EntityObject, IMyEntity { [Key] [DataMember] [Editable(false)] public int DummyKey { get; set; } [DataMember] [Editable(false)] public IEnumerable<SomeOtherEntity> Children { get; set; } } I figure I'm missing something simple here. Could someone please tell me how I can create an invokable method that returns a single MyEntity object?

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  • XmlSerializer - There was an error reflecting type

    - by oo
    Using C# .NET 2.0, I have a composite data class that does have the [Serializable] attribute on it. I am creating an XMLSerializer class and passing that into the constructor: XmlSerializer serializer = new XmlSerializer(typeof(DataClass)); I am getting an exception saying: There was an error reflecting type. Inside the data class there is another composite object. Does this also need to have the [Serializable] attribute or by having it on the top object does it recursively apply it to all objects inside? Any thoughts?

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  • C# inheritance XmlSerializer

    - by ikurtz
    greetngs, i have two classes: [Serializable] public class FireGridUnit { public GridUnit FireGridLocation { get; set; } } [Serializable] public class FireResult: FireGridUnit { public bool Hit { get; set; } public bool ShipDestroyed { get; set; } public Ship.ValidShips DestroyedShipType {get; set;} public bool Win { get; set; } } as you see FireResult inherits FireGrdUnit. in my code when i try to use them i get a runtime error: Unable to cast object of type 'NietzscheBattleships.FireGridUnit' to type 'NietzscheBattleships.FireResult'. is this because if i am serializing the class has to be independant ie not be inherited? many thanks.

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  • JPA entities -- org.hibernate.TypeMismatchException

    - by shane lee
    Environment: JDK 1.6, JEE5 Hibernate Core 3.3.1.GA, Hibernate Annotations 3.4.0.GA DB:Informix Used reverse engineering to create my persistence entities from db schema [NB:This is a schema in work i cannot change] Getting exception when selecting list of basic_auth_accounts org.hibernate.TypeMismatchException: Provided id of the wrong type for class ebusiness.weblogic.model.UserAccounts. Expected: class ebusiness.weblogic.model.UserAccountsId, got class ebusiness.weblogic.model.BasicAuthAccountsId Both basic_auth_accounts and user_accounts have composite primary keys and one-to-one relationships. Any clues what to do here? This is pretty important that i get this to work. Cannot find any substantial solution on the net, some say to create an ID class which hibernate has done, and some say not to have a one-to-one relationship. Please help me!! /** * BasicAuthAccounts generated by hbm2java */ @Entity @Table(name = "basic_auth_accounts", schema = "ebusdevt", catalog = "ebusiness_dev", uniqueConstraints = @UniqueConstraint(columnNames = { "realm_type_id", "realm_qualifier", "account_name" })) public class BasicAuthAccounts implements java.io.Serializable { private BasicAuthAccountsId id; private UserAccounts userAccounts; private String accountName; private String hashedPassword; private boolean passwdChangeReqd; private String hashMethodId; private int failedAttemptNo; private Date failedAttemptDate; private Date lastAccess; public BasicAuthAccounts() { } public BasicAuthAccounts(UserAccounts userAccounts, String accountName, String hashedPassword, boolean passwdChangeReqd, String hashMethodId, int failedAttemptNo) { this.userAccounts = userAccounts; this.accountName = accountName; this.hashedPassword = hashedPassword; this.passwdChangeReqd = passwdChangeReqd; this.hashMethodId = hashMethodId; this.failedAttemptNo = failedAttemptNo; } public BasicAuthAccounts(UserAccounts userAccounts, String accountName, String hashedPassword, boolean passwdChangeReqd, String hashMethodId, int failedAttemptNo, Date failedAttemptDate, Date lastAccess) { this.userAccounts = userAccounts; this.accountName = accountName; this.hashedPassword = hashedPassword; this.passwdChangeReqd = passwdChangeReqd; this.hashMethodId = hashMethodId; this.failedAttemptNo = failedAttemptNo; this.failedAttemptDate = failedAttemptDate; this.lastAccess = lastAccess; } @EmbeddedId @AttributeOverrides( { @AttributeOverride(name = "realmTypeId", column = @Column(name = "realm_type_id", nullable = false, length = 32)), @AttributeOverride(name = "realmQualifier", column = @Column(name = "realm_qualifier", nullable = false, length = 32)), @AttributeOverride(name = "accountId", column = @Column(name = "account_id", nullable = false)) }) public BasicAuthAccountsId getId() { return this.id; } public void setId(BasicAuthAccountsId id) { this.id = id; } @OneToOne(fetch = FetchType.LAZY) @PrimaryKeyJoinColumn @NotNull public UserAccounts getUserAccounts() { return this.userAccounts; } public void setUserAccounts(UserAccounts userAccounts) { this.userAccounts = userAccounts; } /** * BasicAuthAccountsId generated by hbm2java */ @Embeddable public class BasicAuthAccountsId implements java.io.Serializable { private String realmTypeId; private String realmQualifier; private long accountId; public BasicAuthAccountsId() { } public BasicAuthAccountsId(String realmTypeId, String realmQualifier, long accountId) { this.realmTypeId = realmTypeId; this.realmQualifier = realmQualifier; this.accountId = accountId; } /** * UserAccounts generated by hbm2java */ @Entity @Table(name = "user_accounts", schema = "ebusdevt", catalog = "ebusiness_dev") public class UserAccounts implements java.io.Serializable { private UserAccountsId id; private Realms realms; private UserDetails userDetails; private Integer accessLevel; private String status; private boolean isEdge; private String role; private boolean chargesAccess; private Date createdTimestamp; private Date lastStatusChangeTimestamp; private BasicAuthAccounts basicAuthAccounts; private Set<Sessions> sessionses = new HashSet<Sessions>(0); private Set<AccountGroups> accountGroupses = new HashSet<AccountGroups>(0); private Set<UserPrivileges> userPrivilegeses = new HashSet<UserPrivileges>(0); public UserAccounts() { } public UserAccounts(UserAccountsId id, Realms realms, UserDetails userDetails, String status, boolean isEdge, boolean chargesAccess) { this.id = id; this.realms = realms; this.userDetails = userDetails; this.status = status; this.isEdge = isEdge; this.chargesAccess = chargesAccess; } @EmbeddedId @AttributeOverrides( { @AttributeOverride(name = "realmTypeId", column = @Column(name = "realm_type_id", nullable = false, length = 32)), @AttributeOverride(name = "realmQualifier", column = @Column(name = "realm_qualifier", nullable = false, length = 32)), @AttributeOverride(name = "accountId", column = @Column(name = "account_id", nullable = false)) }) @NotNull public UserAccountsId getId() { return this.id; } public void setId(UserAccountsId id) { this.id = id; } @OneToOne(fetch = FetchType.LAZY, mappedBy = "userAccounts") public BasicAuthAccounts getBasicAuthAccounts() { return this.basicAuthAccounts; } public void setBasicAuthAccounts(BasicAuthAccounts basicAuthAccounts) { this.basicAuthAccounts = basicAuthAccounts; } /** * UserAccountsId generated by hbm2java */ @Embeddable public class UserAccountsId implements java.io.Serializable { private String realmTypeId; private String realmQualifier; private long accountId; public UserAccountsId() { } public UserAccountsId(String realmTypeId, String realmQualifier, long accountId) { this.realmTypeId = realmTypeId; this.realmQualifier = realmQualifier; this.accountId = accountId; } @Column(name = "realm_type_id", nullable = false, length = 32) @NotNull @Length(max = 32) public String getRealmTypeId() { return this.realmTypeId; } public void setRealmTypeId(String realmTypeId) { this.realmTypeId = realmTypeId; } @Column(name = "realm_qualifier", nullable = false, length = 32) @NotNull @Length(max = 32) public String getRealmQualifier() { return this.realmQualifier; } public void setRealmQualifier(String realmQualifier) { this.realmQualifier = realmQualifier; } @Column(name = "account_id", nullable = false) public long getAccountId() { return this.accountId; } public void setAccountId(long accountId) { this.accountId = accountId; } Main Code for classes are:

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  • Interfaces with hibernate annotations

    - by molleman
    Hello i am wondering how i would be able to annotate an interface @Entity @Table(name = "FOLDER_TABLE") public class Folder implements Serializable, Hierarchy { @Id @GeneratedValue(strategy = GenerationType.AUTO) @Column(name = "folder_id", updatable = false, nullable = false) private int fId; @Column(name = "folder_name") private String folderName; @OneToMany(cascade = CascadeType.ALL) @JoinTable(name = "FOLDER_JOIN_FILE_INFORMATION_TABLE", joinColumns = { @JoinColumn(name = "folder_id") }, inverseJoinColumns = { @JoinColumn(name = "file_information_id") }) private List< Hierarchy > fileInformation = new ArrayList< Hierarchy >(); above and below are 2 classes that implement an interface called Hierarchy, the folder class has a list of Hierarchyies being a folder or a fileinformation class @Entity @Table(name = "FILE_INFORMATION_TABLE") public class FileInformation implements Serializable, Hierarchy { @Id @GeneratedValue(strategy = GenerationType.AUTO) @Column(name = "file_information_id", updatable = false, nullable = false) private int ieId; @Column (name = "location") private String location; i have serached the web for someway to annotate or a workaround but i cannot map the interface which is simply this public interface Hierarchy { } i get a mapping exeception on the List of hierarchyies with a folder but i dont know how to map the class correctly

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  • Enable 2-way databinding on nested listview

    - by Lars Pedersen
    I have a ASP.NET FormView, that - via an ObjectDataSource - is bound to my EventOrder-object: [Serializable] public class EventOrder { [Serializable] public class OrderTicket { public int Qty { get; set; } public int Id { get { return this.Ticket.Id; } } public Ticket Ticket { get; set; } public double TicketPrice { get; set; } } [Serializable] public class OrderExtra { public int Qty { get; set; } public int Id { get { return this.Extra.Id; } } public Extra Extra { get; set; } } public Event Event { get; set; } public List<OrderTicket> OrderTickets { get; set; } public List<OrderExtra> OrderExtras { get; set; } public UserProfile UserProfile { get; set; } public List<Fee> Fees { get; set; } public List<Discount> Discounts { get; set; } public EventOrder() { this.OrderExtras = new List<OrderExtra>(); this.OrderTickets = new List<OrderTicket>(); this.Fees = new List<Fee>(); this.Discounts = new List<Discount>(); } } In my FormView, I have a bindingexpression on an inner listview for my collection of OrderTickets: <asp:ListView Visible="false" runat="server" DataKeyNames="Id" ID="lvTickets" DataSource='<%# Bind("OrderTickets") %>'> <ItemTemplate> <asp:TextBox ID="TextBox5" Text='<%# Bind("Qty") %>' runat="server"></asp:TextBox> <asp:Label ID="Label1" runat="server" Text='<%# Eval("Ticket.Title") %>'></asp:Label> <asp:Label ID="Label2" runat="server" Text='<%# Eval("TicketPrice") %>'></asp:Label><br /> </ItemTemplate> My problem is that the Qty-property isn't databound to the object when the parent container is updated. Is it possible to have this kind of parent-child relation with 2-way databinding? Can I force the child listview to update it's bound dataobject when I submit the form?

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  • ISerializable and backward compatibility

    - by pierusch
    hello I have to work an an old application that used binaryFormatter to serialize application data into filestream (say in a file named "data.oldformat") without any optimizazion the main class has been marked with attribute <serializable()>public MainClass ....... end class and the serialization code dim b as new binaryformatter b.serialize(mystream,mymainclass) In an attempt to optimize the serialization/deserialization process I simply made the class implement the ISerializable interface and wrote some optimized serialization routines <serializable()>public MainClass implements ISerializable ....... end class The optimization works really well but I MUST find a way to reatrive the data inside the old files for backward compatibility. How can I do that?? Pierluigi

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  • Eclipselink read complex object model in an ordered way

    - by Raven
    Hi, I need to read a complex model in an ordered way with eclipselink. The order is mandantory because it is a huge database and I want to have an output of a small portion of the database in a jface tableview. Trying to reorder it in the loading/quering thread takes too long and ordering it in the LabelProvider blocks the UI thread too much time, so I thought if Eclipselink could be used that way, that the database will order it, it might give me the performance I need. Unfortunately the object model can not be changed :-( The model is something like: @SuppressWarnings("serial") @Entity public class Thing implements Serializable { @Id @GeneratedValue(strategy = GenerationType.TABLE) private int id; private String name; @OneToMany(cascade=CascadeType.ALL) @PrivateOwned private List<Property> properties = new ArrayList<Property>(); ... // getter and setter following here } public class Property implements Serializable { @Id @GeneratedValue(strategy = GenerationType.TABLE) private int id; @OneToOne private Item item; private String value; ... // getter and setter following here } public class Item implements Serializable { @Id @GeneratedValue(strategy = GenerationType.TABLE) private int id; private String name; .... // getter and setter following here } // Code end In the table view the y-axis is more or less created with the query Query q = em.createQuery("SELECT m FROM Thing m ORDER BY m.name ASC"); using the "name" attribute from the Thing objects as label. In the table view the x-axis is more or less created with the query Query q = em.createQuery("SELECT m FROM Item m ORDER BY m.name ASC"); using the "name" attribute from the Item objects as label. Each cell has the value Things.getProperties().get[x].getValue() Unfortunately the list "properties" is not ordered, so the combination of cell value and x-axis column number (x) is not necessarily correct. Therefore I need to order the list "properties" in the same way as I ordered the labeling of the x-axis. And exactly this is the thing I dont know how it is done. So querying for the Thing objects should return the list "properties" "ORDER BY name ASC" but of the "Item"s objects. My ideas are something like having a query with two JOINs. Joing Things with Property and with Item but somehow I was unable to get it to work yet. Thank you for your help and your ideas to solve this riddle.

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  • What's the best Communication Pattern for EJB3-based applications?

    - by Hank
    I'm starting a JEE project that needs to be strongly scalable. So far, the concept was: several Message Driven Beans, responsible for different parts of the architecture each MDB has a Session Bean injected, handling the business logic a couple of Entity Beans, providing access to the persistence layer communication between the different parts of the architecture via Request/Reply concept via JMS messages: MDB receives msg containing activity request uses its session bean to execute necessary business logic returns response object in msg to original requester The idea was that by de-coupling parts of the architecture from each other via the message bus, there is no limit to the scalability. Simply start more components - as long as they are connected to the same bus, we can grow and grow. Unfortunately, we're having massive problems with the request-reply concept. Transaction Mgmt seems to be in our way plenty. It seams that session beans are not supposed to consume messages?! Reading http://blogs.sun.com/fkieviet/entry/request_reply_from_an_ejb and http://forums.sun.com/message.jspa?messageID=10338789, I get the feeling that people actually recommend against the request/reply concept for EJBs. If that is the case, how do you communicate between your EJBs? (Remember, scalability is what I'm after) Details of my current setup: MDB 1 'TestController', uses (local) SLSB 1 'TestService' for business logic TestController.onMessage() makes TestService send a message to queue XYZ and requests a reply TestService uses Bean Managed Transactions TestService establishes a connection & session to the JMS broker via a joint connection factory upon initialization (@PostConstruct) TestService commits the transaction after sending, then begins another transaction and waits 10 sec for the response Message gets to MDB 2 'LocationController', which uses (local) SLSB 2 'LocationService' for business logic LocationController.onMessage() makes LocationService send a message back to the requested JMSReplyTo queue Same BMT concept, same @PostConstruct concept all use the same connection factory to access the broker Problem: The first message gets send (by SLSB 1) and received (by MDB 2) ok. The sending of the returning message (by SLSB 2) is fine as well. However, SLSB 1 never receives anything - it just times out. I tried without the messageSelector, no change, still no receiving message. Is it not ok to consume message by a session bean? SLSB 1 - TestService.java @Resource(name = "jms/mvs.MVSControllerFactory") private javax.jms.ConnectionFactory connectionFactory; @PostConstruct public void initialize() { try { jmsConnection = connectionFactory.createConnection(); session = jmsConnection.createSession(false, Session.AUTO_ACKNOWLEDGE); System.out.println("Connection to JMS Provider established"); } catch (Exception e) { } } public Serializable sendMessageWithResponse(Destination reqDest, Destination respDest, Serializable request) { Serializable response = null; try { utx.begin(); Random rand = new Random(); String correlationId = rand.nextLong() + "-" + (new Date()).getTime(); // prepare the sending message object ObjectMessage reqMsg = session.createObjectMessage(); reqMsg.setObject(request); reqMsg.setJMSReplyTo(respDest); reqMsg.setJMSCorrelationID(correlationId); // prepare the publishers and subscribers MessageProducer producer = session.createProducer(reqDest); // send the message producer.send(reqMsg); System.out.println("Request Message has been sent!"); utx.commit(); // need to start second transaction, otherwise the first msg never gets sent utx.begin(); MessageConsumer consumer = session.createConsumer(respDest, "JMSCorrelationID = '" + correlationId + "'"); jmsConnection.start(); ObjectMessage respMsg = (ObjectMessage) consumer.receive(10000L); utx.commit(); if (respMsg != null) { response = respMsg.getObject(); System.out.println("Response Message has been received!"); } else { // timeout waiting for response System.out.println("Timeout waiting for response!"); } } catch (Exception e) { } return response; } SLSB 2 - LocationService.Java (only the reply method, rest is same as above) public boolean reply(Message origMsg, Serializable o) { boolean rc = false; try { // check if we have necessary correlationID and replyTo destination if (!origMsg.getJMSCorrelationID().equals("") && (origMsg.getJMSReplyTo() != null)) { // prepare the payload utx.begin(); ObjectMessage msg = session.createObjectMessage(); msg.setObject(o); // make it a response msg.setJMSCorrelationID(origMsg.getJMSCorrelationID()); Destination dest = origMsg.getJMSReplyTo(); // send it MessageProducer producer = session.createProducer(dest); producer.send(msg); producer.close(); System.out.println("Reply Message has been sent"); utx.commit(); rc = true; } } catch (Exception e) {} return rc; } sun-resources.xml <admin-object-resource enabled="true" jndi-name="jms/mvs.LocationControllerRequest" res-type="javax.jms.Queue" res-adapter="jmsra"> <property name="Name" value="mvs.LocationControllerRequestQueue"/> </admin-object-resource> <admin-object-resource enabled="true" jndi-name="jms/mvs.LocationControllerResponse" res-type="javax.jms.Queue" res-adapter="jmsra"> <property name="Name" value="mvs.LocationControllerResponseQueue"/> </admin-object-resource> <connector-connection-pool name="jms/mvs.MVSControllerFactoryPool" connection-definition-name="javax.jms.QueueConnectionFactory" resource-adapter-name="jmsra"/> <connector-resource enabled="true" jndi-name="jms/mvs.MVSControllerFactory" pool-name="jms/mvs.MVSControllerFactoryPool" />

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  • Eclipselink read complex oject model in an ordered way

    - by Raven
    Hi, I need to read a complex model in an ordered way with eclipselink. The order is mandantory because it is a huge database and I want to have an output of a small portion of the database in a jface tableview. Trying to reorder it in the loading/quering thread takes too long and ordering it in the LabelProvider blocks the UI thread too much time, so I thought if Eclipselink could be used that way, that the database will order it, it might give me the performance I need. Unfortunately the object model can not be changed :-( The model is something like: @SuppressWarnings("serial") @Entity public class Thing implements Serializable { @Id @GeneratedValue(strategy = GenerationType.TABLE) private int id; private String name; @OneToMany(cascade=CascadeType.ALL) @PrivateOwned private List<Property> properties = new ArrayList<Property>(); ... // getter and setter following here } public class Property implements Serializable { @Id @GeneratedValue(strategy = GenerationType.TABLE) private int id; @OneToOne private Item item; private String value; ... // getter and setter following here } public class Item implements Serializable { @Id @GeneratedValue(strategy = GenerationType.TABLE) private int id; private String name; .... // getter and setter following here } // Code end In the table view the y-axis is more or less created with the query Query q = em.createQuery("SELECT m FROM Thing m ORDER BY m.name ASC"); using the "name" attribute from the Thing objects as label. In the table view the x-axis is more or less created with the query Query q = em.createQuery("SELECT m FROM Item m ORDER BY m.name ASC"); using the "name" attribute from the Item objects as label. Each cell has the value Things.getProperties().get[x].getValue() Unfortunately the list "properties" is not ordered, so the combination of cell value and x-axis column number (x) is not necessarily correct. Therefore I need to order the list "properties" in the same way as I ordered the labeling of the x-axis. And exactly this is the thing I dont know how it is done. So querying for the Thing objects should return the list "properties" "ORDER BY name ASC" but of the "Item"s objects. My ideas are something like having a query with two JOINs. Joing Things with Property and with Item but somehow I was unable to get it to work yet. Thank you for your help and your ideas to solve this riddle.

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  • Spring WS & Validator interceptor

    - by mada
    I have a endpoint mapping a webservice which is used to insert in the dabatabase some keywords: @Transactional(readOnly = false,isolation= Isolation.SERIALIZABLE) public Source saveKW(...). The input is a request. I would like to add an interceptor on the method in order to validate the parameters. this one will read some values from the DB. i would like that this interceptor is EMBED in the transaction declared for the endpoint (or this opposite). In other words, i want them to be in the same transaction. Ideally im looking for something like this with annotation: @Transactional(readOnly = false,isolation= Isolation.SERIALIZABLE) @validator("KeyWordValidaor.class") public Source saveKW(...) where KeyWordValidaor will be class validating the parameters. Have you any idea or short examples to implements this like this way or in a other real way?

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  • Strange problem with SEAM stateful session bean

    - by John
    Hi, I've got a staeful session bean. @Scope(ScopeType.SESSION) @Name("chuckNorrisBean") public class ChuckNorrisBean implements Serializable, ChuckNorris with some function public void roundHouseKick() { ... } interface @Local public interface ChuckNorris { public void roundHouseKick() { ... } } and calling them on a jsf .xhtml page using #{chuckNorrisBean.roundHouseKick} which works perfectly fine. However if I add the @Stateful annotation to the bean so it becomes @Stateful @Scope(ScopeType.SESSION) @Name("chuckNorrisBean") public class ChuckNorrisBean implements Serializable, ChuckNorris and the page will load with exceptions complainig about Exception during request processing:Caused by javax.servlet.ServletException with message: "#{chuckNorrisBean.roundHouseKick}: javax.el.MethodNotFoundException: //localhost/universe/earth.xhtml @41,65 action= "#{chuckNorrisBean.roundHouseKick}": Method not found: ChuckNorrisBean:a6gkg-w6das4-g8wmgh0y-1-g8woy0wo-4b.roundHouseKick()" Any advice on what might've went wrong with my chuckNorrisBean? The system is built on SEAM/richfaces. Thanks!

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  • In VB.NET how do you specify Inherits/implements on a generic class with multi-constraints

    - by Romel Evans
    When I write the following statement in VB.Net (C# is my normal language), I get an "end of statement expected" referring to the "Implements" statement. <Serializable()> _ <XmlSchemaProvider("EtgSchema")> _ Public Class SerializeableEntity(Of T As {Class, ISerializable, New}) _ Implements IXmlSerializable, ISerializable ... End Class The C# version that I'm trying to emulate is: [Serializable] [XmlSchemaProvider("MySchema")] public class SerializableEntity<T> : IXmlSerializable, ISerializable where T : class, new() { .... } Sometimes I feel like I have 5 thumbs with VB.NET :)

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  • versioning fails for onetomany collection holder

    - by Alexander Vasiljev
    given parent entity @Entity public class Expenditure implements Serializable { ... @OneToMany(mappedBy = "expenditure", cascade = CascadeType.ALL, orphanRemoval = true) @OrderBy() private List<ExpenditurePeriod> periods = new ArrayList<ExpenditurePeriod>(); @Version private Integer version = 0; ... } and child one @Entity public class ExpenditurePeriod implements Serializable { ... @ManyToOne @JoinColumn(name="expenditure_id", nullable = false) private Expenditure expenditure; ... } While updating both parent and child in one transaction, org.hibernate.StaleObjectStateException is thrown: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect): Indeed, hibernate issues two sql updates: one changing parent properties and another changing child properties. Do you know a way to get rid of parent update changing child? The update results both in inefficiency and false positive for optimistic lock. Note, that both child and parent save their state in DB correctly. Hibernate version is 3.5.1-Final

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