=============================================================================== Managed Data Structures Copyright © 2016 Hewlett Packard Enterprise Development Company LP.
Author: Susan Spence ([email protected])
Contributors: Evan Kirshenbaum, Susan Spence, Lokesh Gidra, Abraham Alcantara, Sergio Gonzalez, Sergei Uversky.
The Managed Data Structures library delivers a simple, high-level programming model for persistent memory. It is designed to take full advantage of the large, random-access, non-volatile memory and highly-parallel processing of The Machine and other persistent memory architectures. Application programmers use and persist their data directly in their application, in common data structures such as lists, maps and graphs, and the MDS library manages this data. The library supports multi-threaded, multi-process creation, use and sharing of managed data structures, via APIs in multiple programming languages, Java and C++.
Releases of the MDS source code are available open source on GitHub: https://github.com/HewlettPackard/mds
Maturity: Alpha.
The Managed Data Structures software library has been developed as part of the Managed Data Structures research project at Hewlett Packard Labs. As such, releases of the MDS source code made available on GitHub are not production quality, but rather "alpha" quality. The MDS APIs have been specified and they have been implemented sufficiently to demonstrate proof of concept so far. However, MDS is not functionally complete; we have documented which APIs have not yet been implemented, and an attempt to call an implemented method will result in a "stub not implemented" error message. MDS releases have gone through basic testing, but may be unstable and could cause crashes or data loss.
MDS is an active research project; we intend to make further releases with more and/or better features and bug fixes as the project continues.
Managed Data Structures is distributed under the LGPLv3 license with an exception. See license files COPYING and COPYING.LESSER.
Multi-Process Garbage Collector: https://github.com/HewlettPackard/mpgc
Documentation on The Managed Data Structures Library: Java API is available on the MDS GitHub site: https://github.com/HewlettPackard/mds/blob/master/doc/MDS%20Java%20API.pdf
The Managed Data Structures Library: C++ API is available on the MDS GitHub site: https://github.com/HewlettPackard/mds/blob/master/doc/MDS%20C++%20API.pdf
The user guides describe in detail how Java and C++ applications can create and use managed data structures in an MDS managed heap, using the MDS Java API, and how they can safely share those data structures between processes, using high-level transactional support provided by the MDS library.
Here are a few simple code examples, to illustrate some basic use of MDS. These examples use the MDS Java API.
A programmer creates a managed data structure using the MDS API. For example, using the MDS Java API, the programmer can write code in their Java application to create a ManagedArray of integers:
ManagedIntArray inventory_i = ManagedInt.TYPE.createArray(size);
- Managed Space. When a programmer creates a managed data structure, like this ManagedArray, MDS allocates this object directly in the MDS Managed Space. This Managed Space is one large virtual pool of memory; a shared, persistent heap in which MDS allocates and manages MDS application objects, with the help of the Multi-Process Garbage Collector.
- Create object. Note that MDS objects are allocated in the MDS Managed Space using create method calls on an object type; in contrast with a programmer calling the new method to create a standard Java object in the Java single-process volatile heap.
- Typed object. Note also that all MDS objects are strongly typed, so that the programmer always knows what type of object they are dealing with. An object is typically created with a well-defined type, by creating it via a create method on the object type itself. In the case of managed arrays, managed types support a createArray method to create a managed array of that type: thus, ManagedInt.TYPE, the managed type for integers in MDS, supports a createArray method call to create instances of ManagedIntArray, for managed arrays of integers.
- Supported types. MDS is designed to support primitive types, strings, data structures and records, and it enables users to specify their own record types composed of these MDS supported types.
- Records via annotations. To avoid the user having to write a lot of boiler-plate code for a ManagedRecord type, MDS provides support for high-level specification of a ManagedRecord type using Java annotations; the programmer then runs an annotations processor provided with MDS to automatically generate a lot of the standard code for accessing and using objects of that ManagedRecord type.
The programmer uses an MDS object just like a standard Java object in a Java application.
They can populate an MDS data structure with elements.
inventory_i.set(0,0);
inventory_i.set(1,1);
inventory_i.set(2,2);
The MDS Java API supports a style of programming that is close to that of standard Java code, as much as possible. Thus, we have defined ManagedIntArray so that it can take integers directly as arguments.
However, given that a ManagedIntArray is really a managed array of ManagedInt elements, the programmer could also write equivalent code to create a ManagedInt object, using a call to a create method on the type as described before, and set an element of the ManagedIntArray to reference this new ManagedInt object.
ManagedInt intElement = ManagedInt.Type.create(1);
inventory_i.set(1,intElement);
Then the programmer can use the ManagedArray and its elements, writing very similar code to standard Java. They can get and set elements of the array:
ManagedInt productCount = inventory_i.get(2);
newCount = productCount.asInt() - countDecr;
inventory_i.set(2, newCount);
They can iterate through the array elements:
int total = 0;
for (ManagedInt i: inventory_i) {
System.out.println("inventory: i: " + i.asInt());
total += i.asInt();
System.out.println("total so far: " + total);
}
System.out.println("Total inventory: " + total);
To make an MDS object accessible beyond the process that creates it, we bind the object to a name in the MDS namespace.
inventory_i.bindName("inventory_i");
A different application process can then look up the same MDS object by name, either concurrently or long after the original creator process has finished, and get back a reference to it in the MDS Managed Space.
ManagedIntArray inventory_i = ManagedIntArray.TYPE.lookupName("inventory_i");
MDS enables programmers to specify their own record types composed of the MDS supported types, as mentioned above. To avoid the user having to write a lot of boiler-plate code for a ManagedRecord type, MDS provides support for high-level specification of a ManagedRecord type using Java annotations; the programmer then runs an annotations processor provided with MDS to automatically generate a lot of the standard code for accessing and using objects of that ManagedRecord type. The MDS user guide goes into detail about how a programmer defines the basics of a record type and runs it through the annotations processor to get a complete definition. To keep this introduction to MDS usage simple, we elide the details of record type definition here and focus on a simple example of usage.
Following on from our initial example, showing creation and use of a managed array of integers, the creation and use of a managed array of ManagedRecord objects looks very similar. Given a ManagedRecord definition for a Product type, the code for creating a managed array of Product objects is:
ManagedArray<Product> inventory_p = Product.TYPE.createArray(size);
Product product = null;
product = Product.create.record("A4 Art Pad", 100, 200);
inventory_p.set(0,product);
product = Product.create.record("Pencil HB", 1000, 10);
inventory_p.set(1,product);
product = Product.create.record("English Oxford Dictionary", 50, 450);
inventory_p.set(2,product);
Atomic operations. To make a simple modification to a managed object, we can use atomic operations supported on that object:
Product product = inventory_p.get(2);
product.decCount(1);
Transactional IsolationContext. To make an update to a managed object, that might potentially conflict with an update being made concurrently by another thread or process, we can isolate the update in an MDS transactional IsolationContext:
isolated(() -> {
inventory_p.set(1, null);
});
Snapshots. To run an analysis on managed objects, while other threads or processes may be updating them concurrently, we can run the analysis on a light-weight, zero-copy snapshot of the data:
inReadOnlySnapshot(() -> {
int total = 0;
for (Product p: inventory_p) {
if (p != null) {
total += p.getCount();
}
}
System.out.println("Total inventory count: " + total);
});
MDS runs and has been tested on x86 and ARM architectures.
To compile a Java application that uses MDS, the programmer uses the JAR files for the MDS Java API.
Details for compiling MDS can be found in INSTALL.md. The basics are as follows...
Assuming MDS and its dependency MPGC have been cloned to the same top-level directory, to compile sources for MDS:
cd mds/java-api
ant -f build-all.xml
To compile sources for MDS Inventory demo: follow instructions in mds/demo/inventory/README.md
The programmer loads the MDS library dynamically during the initial execution of their Java program, by invoking System.loadLibrary from a static code block:
static {
System.loadLibrary("mds-jni");
}
The programmer then uses the MDS Java API by simply invoking method calls to methods of the MDS Java API classes.
Full details of how to use the MDS library are described in our user guide and illustrated in demo code supplied as part of the MDS open source release.
To compile a C++ application that uses MDS, assuming that <install>
refers to the directory that was the target of make install
(typically install as a sibling of mds and mpgc):
-
The source files should be compiled with
-I<install>/include. -
The program must link against the following libraries
<install>/lib/libmds-cpp.a<install>/lib/libmds_core.a<install>/lib/libmpgc.a<install>/lib/libruts.a
-
The source code must
#include "mds.h"MDS can be used for object management and sharing by multiple application processes using a shared object heap in shared (volatile) memory: the MDS Managed Space is a file mmapped into memory and, on normal process shutdown, changes to objects in Managed Space will be written back to that file. However, MDS is really designed to deliver the benefits of persistent memory programming on The Machine and other persistent memory architectures. To benefit from the fault-tolerant aspects of MDS (and its fault-tolerant automatic memory management provided by MPGC), where MDS object state is maintained consistently in the face of process and system failures, MDS should be run in a system with persistent memory where caches are flushed on failure; otherwise, we do not guarantee that the heap will be uncorrupted after failures.
Limitations. MDS currently supports only a limited number of managed types: it supports primitives, strings, user-defined managed records, and managed arrays of primitives, strings and records. Managed arrays of managed arrays are not yet supported.
Known bugs. We know that the current MDS release has memory leaks as a result of holding on to the entire version history of objects. This will be addressed in future releases.
- The Multi Process Garbage Collector, which is used by MDS for its automatic memory management: https://github.com/HewlettPackard/mpgc
Other tools for programming with non-volatile memory include:
- Atlas: Fault-tolerant programming model for non-volatile memory
- FOEDUS: Fast optimistic engine for data unification services
-
1.0 2016-11-15
- Initial release. MDS core. Java API
-
2.0 2017-08-07
- Added C++ API
- Significant internal redesign for performance and correctness.