Shallow & Retained Heap Size Calculation - By gceasy I have shared many tips related to heap dump analysis in the past. To continue the treasure of performance engineering related to heap dump, today I am sharing an article which described the calculation of shallow and retained heap size in a very simple way along with the examples (especially.
Particle size grading. Historically a sequential series of screens was used to sort particle sizes. Each of these screens has a differing number of wires and openings per inch. As material passes through one screen and is retained on another we can sort them into size categories. ANSI B74.12 defines the size distribution of particles.
A sieve analysis (or gradation test) is a practice or procedure used in civil engineering and chemical engineering to assess the particle size distribution (also called gradation) of a granular material by allowing the material to pass through a series of sieves of progressively smaller mesh size and weighing the amount of material that is stopped by each sieve as a fraction of the whole mass.

Yourkit Retained Size Vs Shallow Size
Shallow Size Vs Retained Size Chart
Shallow Size Vs Retained Size Chart
Shallow Size Vs Retained Size Model

Feb 13, 2019 Shallow Heap Size. Remember: the shallow heap of an object is its size in the memory. Since, in our example, each object occupies about 10 bytes, the shallow heap size of each object is 10 bytes. Retained Heap Size of B. From Fig #1, you can notice that object B is holding a reference to objects D and E.

YourKit Java Profiler is capable of measuring shallow and retained sizes of objects.

Shallow size of an object is the amount of memory allocated to store the object itself, not taking into account the referenced objects. Shallow size of a regular (non-array) object depends on the number and types of its fields. Shallow size of an array depends on the array length and the type of its elements (objects, primitive types). Shallow size of a set of objects represents the sum of shallow sizes of all objects in the set.

Retained size of an object is its shallow size plus the shallow sizes of the objects that are accessible, directly or indirectly, only from this object. In other words, the retained size represents the amount of memory that will be freed by the garbage collector when this object is collected.

Shallow size vs retained size conversion

To better understand the notion of the retained size, let us look at the following examples:

In order to measure the retained sizes, all objects in memory are treated as nodes of a graph where its edges represent references from objects to objects. There are also special nodes - GC root objects, which will not be collected by Garbage Collector at the time of measuring (read more about GC roots).

The pictures below show the same set of objects, but with varying internal references.

Figure 2:

Let us consider obj1.
As you can see, in both pictures we have highlighted all of the objects that are directly or indirectly accessed only by obj1. If you look at Figure 1, you will see that obj3 is not highlighted, because it is also referenced by a GC root object. On Figure 2, however, it is already included into the retained set, unlike obj5, which is still referenced by GC root.

Thus, the retained size of obj1 will represent the following respective values:

For Figure 1: the sum of shallow sizes of obj1, obj2 and obj4
For Figure 2: the sum of shallow sizes of obj1, obj2, obj3 and obj4

Looking at obj2, however, we see that its retained size in the above cases will be:

For Figure 1: the sum of shallow sizes of obj2 and obj4
For Figure 2: the sum of shallow sizes of obj2, obj3 and obj4

In general, retained size is an integral measure, which helps to understand the structure (clustering) of memory and the dependencies between object subgraphs, as well as find potential roots of those subgraphs.

In this article, we look at the three different sizes that objects can be in a heap analysis, and what this means for your performance.

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If you ever worked with heap analysis, you might have encountered terms such as shallow, retained, and deep size of an object. It doesn’t really matter if we’re talking about analyzing a JVM heap dump with VisualVM or a JavaScript heap snapshot with Chrome DevTools – the terms are the same. The difference between shallow, retained, and deep size is rather straightforward and it can be easily depicted with the following images:

Shallow size – size of the object itself including only references to other objects, without objects which are referenced.

Yourkit Retained Size Vs Shallow Size

Retained size – size of the object including references to other objects and objects which are referenced, but are not shared with any other objects. In other words, the retained memory of an object is the amount of memory that would be freed if the object A was eligible to be collected by GC. Memory of the object E couldn’t be freed because it is also an instance variable of object B.

Deep size – size of the object including references to other objects and objects which are referenced, even if they are shared with other objects.

Shallow Size Vs Retained Size Chart

performance,memory management,heap dump,heap

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Shallow Size Vs Retained Size Chart

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In this article, we look at the three different sizes that objects can be in a heap analysis, and what this means for your performance.

Yourkit Retained Size Vs Shallow Size

Shallow Size Vs Retained Size Chart

Shallow Size Vs Retained Size Chart

Shallow Size Vs Retained Size Model

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