Awesome
MAT Calcite plugin
About
This plugin for Eclipse Memory Analyzer allows to query heap dump via SQL
While MAT does have a query language, it does NOT allow to join, sort and group results. MAT Calcite plugin allows all the typical SQL operations (joins, filters, group by, order by, etc)
Query engine is implemented via Apache Calcite See Calcite SQL reference
Installation
Requirements: Java 17+, Eclipse Memory Analyzer 0.14.0+
There are two update channels:
- https://vlsi.github.io/mat-calcite-plugin-update-site/stable (stable releases)
- https://vlsi.github.io/mat-calcite-plugin-update-site/ea (early access, per-commit releases)
To install Calcite SQL plugin, perform the following:
- Open
Help
,Install New Software...
- Click
Add
, it will open aAdd Repository
window - Type
Calcite SQL plugin stable releases
to theName
field - Type
https://vlsi.github.io/mat-calcite-plugin-update-site/stable/
to theLocation
field - Click
Ok
- All the checkboxes can be left by default (
Show only latest version
,Group items by category
, ...) - Check
SQL for Memory Analyzer
category - Click
Next
(Available Software) - Click
Next
(Installation Details) - Accept License
- Click
Finish
and restart MAT
Early access versions
Development builds are pushed to https://vlsi.github.io/mat-calcite-plugin-update-site/ea/ repository, so you can preview the upcoming version right after the commit lands to the default branch.
Sample
Query that lists duplicate URLs:
select toString(file) file_str, count(*) cnt, sum(retainedSize(this)) sum_retained, sum(shallowSize(this)) sum_shallow
from java.net.URL
group by toString(file)
having count(*)>1
order by sum(retainedSize(this)) desc
To get an explain plan, use "explain plan for select ...":
EnumerableSort(sort0=[$2], dir0=[DESC])
View (expr#0..3=[{inputs}], expr#4=[1], expr#5=[>($t1, $t4)], proj#0..3=[{exprs}], $condition=[$t5])
EnumerableAggregate(group=[{0}], cnt=[COUNT()], sum_retained=[$SUM0($1)], sum_shallow=[$SUM0($2)])
View (expr#0=[{inputs}], expr#1=[0], expr#2=[GET_SNAPSHOT($t1)], expr#3=[GET_IOBJECT($t2, $t0)], expr#4=['file'], expr#5=[RESOLVE_REFERENCE($t3, $t4)], expr#6=[toString($t5)], expr#7=[TO_REFERENCE($t3)], expr#8=[retainedSize($t7)], expr#9=[shallowSize($t7)], file=[$t6], $f1=[$t8], $f2=[$t9])
GetObjectIdsByClass (class=java.net.URL)
Join sample
select u.this, retainedSize(s.this)
from "java.lang.String" s
join "java.net.URL" u
on s.this = u.path
Here's execution plan:
View (expr#0..2=[{inputs}], expr#3=[retainedSize($t2)], this=[$t0], EXPR$1=[$t3])
HashJoin (condition=[=($1, $2)], joinType=[inner])
View (expr#0=[{inputs}], expr#1=[0], expr#2=[GET_SNAPSHOT($t1)], expr#3=[GET_IOBJECT($t2, $t0)], expr#4=[TO_REFERENCE($t3)], expr#5=['path'], expr#6=[RESOLVE_REFERENCE($t3, $t5)], this=[$t4], path=[$t6])
GetObjectIdsByClass (class=java.net.URL)
View (expr#0=[{inputs}], expr#1=[0], expr#2=[GET_SNAPSHOT($t1)], expr#3=[GET_IOBJECT($t2, $t0)], expr#4=[TO_REFERENCE($t3)], this=[$t4])
GetObjectIdsByClass (class=java.lang.String)
Heap schema
heap (default schema)
+- java (sub-schema name)
+- util (sub-schema name)
+- HashMap (table name).
This "table" would return all the instances of java.util.HashMap without subclasses
+- instanceof
+- java
+- util
+- HashMap (table name).
This would return HashMap instances as well as subclass instances (e.g. LinkedHashMap)
+- "java.util.HashMap" (table name)
This can be used as alternative.
+- native.ThreadStackFrames (table name)
Returns thread stack traces and local variable info
Each java class maps to a table. The table lists instances without subclasses
For instance: "java.lang.Object", "java.lang.String" Note: you need to use double quotes to quote identifiers Note: it is assumed that classes sharing the same name have the same fields
The fields become columns.
The following special columns are added:
this | reference to current object
Fields are available as MAP.get call:
select path -- retrieve field as usual
, this['path'] -- retrieve field via MAP get
, this['@className']
, this['@class']['@classLoader'] -- nested calls work as well
from java.net.URL
The following virtual properties are available via MAP.get:
@shallow | shallow heap size of referenced object
@retained | retained heap size for referenced object
@class | the same as `getClass()` in Java
@className | class name (the same as `getClass().getName()` in Java)
The following virtual properties are available for Class
instances via MAP.get:
@super | super class
@classLoader | returns `ClassLoader` for a given class
The following functions can be used to work with column which represents reference:
getId | internal object identifier for referenced object
getAddress | memory address for referenced object
getType | class name of referenced object
toString | textual representation of referenced object
shallowSize | shallow heap size of referenced object
retainedSize | retained heap size for referenced object
length | length of referenced array
getSize | size of referenced collection, map or count of non-null elements in array
getByKey | extracts value for given string representation of key for referenced map
getField | obtains value of field with specified name for referenced object
getStaticField | obtains value of static field with specified name for referenced class
getStringContent | pretty prints object representation
The following table functions are supported:
getRetainedSet(ref) | returns the set of retained objects
getOutboundReferences(ref) | returns outbound references (name, this) pairs
getInboundReferences(ref) | returns inbound references (this)
getValues(ref) | returns all values of a Java collection
getMapEntries(ref) | unnests Map as (key, value) tuples
These functions can be called in a following way:
select
u.this, refs.name, refs.this reference
from
java.net.URL u,
lateral table(getOutboundReferences(u.this)) refs
Another example:
select
p.this, vals.key, vals."value"
from
java.util.Properties p,
lateral table(getMapEntries(p.this)) vals
The following collection functions are also supported:
asMap(ref) | converts Java Map to SQL MAP, so it can be used like asMap(ref)['key']
asMultiSet(ref) | converts Java Collection to SQL MULTISET type
asArray(ref) | converts Java references array to SQL ARRAY type
asByteArray(ref) | converts Java bytes array (bytes[]) to SQL ARRAY type
asShortArray(ref) | converts Java shorts array (short[]) to SQL ARRAY type
asIntArray(ref) | converts Java ints array (int[]) to SQL ARRAY type
asLongArray(ref) | converts Java longs array (long[]) to SQL ARRAY type
asBooleanArray(ref) | converts Java boolean array (boolean[]) to SQL ARRAY type
asCharArray(ref) | converts Java chars array (char[]) to SQL ARRAY type
asFloatArray(ref) | converts Java floats array (float[]) to SQL ARRAY type
asDoubleArray(ref) | converts Java doubles array (double[]) to SQL ARRAY type
These functions can be called in a following way:
select
p.this
from
java.util.Properties p
where
asMap(p.this)['java.vm.version'] is not null
Another example:
select
fpc.this,
fp.fp_ref
from
java.io.FilePermissionCollection fpc,
unnest(asMultiSet(fpc.perms)) fp(fp_ref)
Note, that SQL arrays are indexed starting with '1', so following example shows how to get first element of long[] arrays:
select
asLongArray(all_long_arrays.this)[1] first_element
from
"long[]" all_long_arrays
where
length(all_long_arrays.this) > 0
Array index could be extracted into the table by using the 'unnest ... with ordinality' clause:
select
c.this,
cs.index,
cs.val
from
java.util.GregorianCalendar c,
unnest(asIntArray(c.stamp)) with ordinality cs(val, index)
Requirements
Java 17 as a build JDK. The code can use all Java 17 features. Eclipse Memory Analyzer 0.14.0 or higher
Building
Eclipse plugin cannot depend on jars from maven repository. It has to be a OSGi bundle, however Calcite is easier to reach via maven. So we use two-phase approach: bundle the dependencies in a single jar, then use this jar in eclipse project.
-
Build the plugin
./mvnw install # from the top-level folder
The final repository (aka "update site") with the plugin will be created in
MatCalciteRepository/target/MatCalciteRepository-....zip
Running
It is not yet clear how to run the plugin via maven.
To launch via Eclipse, just open Eclipse project, double-click plugin.xml
, then click Launch an Eclipse application
.
Commandline mode
You can process a single SQL via command line as follows
./MemoryAnalyzer -application MatCalcitePlugin.execute <heap-dump.file> <query.file> <result.file>
Roadmap
- enhance heap schema
- context menu support
- heap-related filtering operators (instance of, dominator of, etc)
- interoperation with mat queries (histogram, retained set, etc)
- support external data providers (e.g. allow to join heapdump objects with csv file)
- projection support (do not compute unnecessary columns)
- optimizer rules
License
This library is distributed under terms of Apache 2 License
Author
Vladimir Sitnikov sitnikov.vladimir@gmail.com