Re: Queries regarding RDFs with Flink
Hi to all, I made a simple RDF Gelly test and I shared it on my github repo at https://github.com/fpompermaier/rdf-gelly-test. I basically setup the Gelly stuff but I can't proceed and compute the drafted TODOs. Could someone help me and implementing them..? I think this could become a nice example of how Gelly could help in handling RDF graphs :) Best, Flavio On Mon, Mar 23, 2015 at 10:41 AM, Flavio Pompermaier pomperma...@okkam.it wrote: Thanks Vasiliki, when I'll find the time I'll try to make a quick prototype using the pointers you suggested! Thanks for the support, Flavio On Mon, Mar 23, 2015 at 10:31 AM, Vasiliki Kalavri vasilikikala...@gmail.com wrote: Hi Flavio, I'm not familiar with JSON-LD, but as far as I understand, you want to generate some trees from selected root nodes. Once you have created the Graph as Andra describes above, you can first filter out the edges that are of no interest to you, using filterOnEdges. There is a description of how edge filtering works in the Gelly docs [1]. Then, you could use a vertex-centric iteration and propagate a message from the selected root node to the neighbors recursively, until you have the tree. In the vertex-centric model, you program from the perspective of a vertex in the graph. You basically need to define what each vertex does within each iteration (superstep). In Gelly this boils down to two things: (a) what messages this vertex will send to its neighbors and (b) how a vertex will update its value using the received messages. This is also described in the Gelly docs [2]. Also, take a look at the Gelly library [3]. The library methods are implemented using this model and should give you an idea. In your case, you will probably need to simply propagate one message from the root node and gather the newly discovered neighbors in each superstep. I hope this helps! Let us know if you have further questions! -Vasia. [1]: http://ci.apache.org/projects/flink/flink-docs-master/gelly_guide.html#graph-transformations [2]: http://ci.apache.org/projects/flink/flink-docs-master/gelly_guide.html#vertex-centric-iterations [3]: http://github.com/apache/flink/tree/master/flink-staging/flink-gelly/src/main/java/orgThehveflink/graph/library
Re: Queries regarding RDFs with Flink
Ok, so, exactly as I wrote a few e-mails back in this thread, you can do
this with a vertex-centric iteration :-)
All you need to do is call myGraph.runVertexCentricIteration(new
MyUpdateFunction(), new MyMessagingFunction(), maxIterations)
and define MyUpdateFunction and MyMessagingFunction.
The first function defines how a vertex updates its value based on the
received messages, while the second defines what messages a vertex sends in
each superstep.
Inside both functions, you have access to the vertex ID and value, so you
can check whether it's the vertex you're interested in.
In your case, in the first superstep, the Person vertex sends a message to
its neighbors​.
You can do this with something like the following inside the the
sendMessages() method:
for (EdgeK, V edge : getOutgoingEdges()) {
sendMessageTo(edge.getTarget(), msg);
}
The rest of the vertices don't need to do anything in the first superstep.
In the next supersteps, the vertices which have received a message,
propagate it to their neighbors in the same way.
One thing you need to be careful about is detecting cycles, so that the
iteration terminates. One way to do this is to mark the vertices you visit,
e.g. by setting a flag in the vertex value and not propagate messages from
a visited vertex.
If you are totally unfamiliar with the vertex-centric model, it might be a
good idea to first do some reading on this, in order to understand how it
works, for example take a look at the Pregel paper [1].
Let us know how it goes!
Cheers,
-Vasia.
[1]: http://kowshik.github.io/JPregel/pregel_paper.pdf
On 14 April 2015 at 18:12, Flavio Pompermaier pomperma...@okkam.it wrote:
Hi Vasia,
for compute subgraph for Person I mean exactly all the vertices that
can be reached
starting from this node and following the graph edges.
I drafted the graph as a set of vertices (where the id is the subject of
the set of triples and the value is all of its triples)
and a set of edges (properties connecting two vertices, this is only
possible if the object is an URI).
Thus, once computed the subgraph of a Person, if I merge the values of all
reachable vertices, I'll obtain all the triples of such a subgraph.
On Tue, Apr 14, 2015 at 4:55 PM, Vasiliki Kalavri
vasilikikala...@gmail.com
wrote:
Hi Flavio,
I'm not quite familiar with RDF or sparql, so not all of your code is
clear
to me.
Your first TODO is compute subgraph for Person. Is Person a vertex id
in your graph? A vertex value?
And by subgraph of Person, do you mean all the vertices that can be
reached starting from this node and following the graph edges?
-Vasia.
On 14 April 2015 at 10:37, Flavio Pompermaier pomperma...@okkam.it
wrote:
Hi to all,
I made a simple RDF Gelly test and I shared it on my github repo at
https://github.com/fpompermaier/rdf-gelly-test.
I basically setup the Gelly stuff but I can't proceed and compute the
drafted TODOs.
Could someone help me and implementing them..?
I think this could become a nice example of how Gelly could help in
handling RDF graphs :)
Best,
Flavio
On Mon, Mar 23, 2015 at 10:41 AM, Flavio Pompermaier
pomperma...@okkam.it
wrote:
Thanks Vasiliki,
when I'll find the time I'll try to make a quick prototype using the
pointers you suggested!
Thanks for the support,
Flavio
On Mon, Mar 23, 2015 at 10:31 AM, Vasiliki Kalavri
vasilikikala...@gmail.com wrote:
Hi Flavio,
I'm not familiar with JSON-LD, but as far as I understand, you want
to
generate some trees from selected root nodes.
Once you have created the Graph as Andra describes above, you can
first
filter out the edges that are of no interest to you, using
filterOnEdges.
There is a description of how edge filtering works in the Gelly docs
[1].
Then, you could use a vertex-centric iteration and propagate a
message
from
the selected root node to the neighbors recursively, until you have
the
tree.
In the vertex-centric model, you program from the perspective of a
vertex
in the graph. You basically need to define what each vertex does
within
each iteration (superstep). In Gelly this boils down to two things:
(a) what messages this vertex will send to its neighbors and
(b) how a vertex will update its value using the received messages.
This is also described in the Gelly docs [2].
Also, take a look at the Gelly library [3]. The library methods are
implemented using this model and should give you an idea.
In your case, you will probably need to simply propagate one message
from
the root node and gather the newly discovered neighbors in each
superstep.
I hope this helps! Let us know if you have further questions!
-Vasia.
[1]:
http://ci.apache.org/projects/flink/flink-docs-master/gelly_guide.html#graph-transformations
Re: Queries regarding RDFs with Flink
Hi Flavio, I'm not quite familiar with RDF or sparql, so not all of your code is clear to me. Your first TODO is compute subgraph for Person. Is Person a vertex id in your graph? A vertex value? And by subgraph of Person, do you mean all the vertices that can be reached starting from this node and following the graph edges? -Vasia. On 14 April 2015 at 10:37, Flavio Pompermaier pomperma...@okkam.it wrote: Hi to all, I made a simple RDF Gelly test and I shared it on my github repo at https://github.com/fpompermaier/rdf-gelly-test. I basically setup the Gelly stuff but I can't proceed and compute the drafted TODOs. Could someone help me and implementing them..? I think this could become a nice example of how Gelly could help in handling RDF graphs :) Best, Flavio On Mon, Mar 23, 2015 at 10:41 AM, Flavio Pompermaier pomperma...@okkam.it wrote: Thanks Vasiliki, when I'll find the time I'll try to make a quick prototype using the pointers you suggested! Thanks for the support, Flavio On Mon, Mar 23, 2015 at 10:31 AM, Vasiliki Kalavri vasilikikala...@gmail.com wrote: Hi Flavio, I'm not familiar with JSON-LD, but as far as I understand, you want to generate some trees from selected root nodes. Once you have created the Graph as Andra describes above, you can first filter out the edges that are of no interest to you, using filterOnEdges. There is a description of how edge filtering works in the Gelly docs [1]. Then, you could use a vertex-centric iteration and propagate a message from the selected root node to the neighbors recursively, until you have the tree. In the vertex-centric model, you program from the perspective of a vertex in the graph. You basically need to define what each vertex does within each iteration (superstep). In Gelly this boils down to two things: (a) what messages this vertex will send to its neighbors and (b) how a vertex will update its value using the received messages. This is also described in the Gelly docs [2]. Also, take a look at the Gelly library [3]. The library methods are implemented using this model and should give you an idea. In your case, you will probably need to simply propagate one message from the root node and gather the newly discovered neighbors in each superstep. I hope this helps! Let us know if you have further questions! -Vasia. [1]: http://ci.apache.org/projects/flink/flink-docs-master/gelly_guide.html#graph-transformations [2]: http://ci.apache.org/projects/flink/flink-docs-master/gelly_guide.html#vertex-centric-iterations [3]: http://github.com/apache/flink/tree/master/flink-staging/flink-gelly/src/main/java/orgThehveflink/graph/library
Re: Queries regarding RDFs with Flink
Hi Vasia, for compute subgraph for Person I mean exactly all the vertices that can be reached starting from this node and following the graph edges. I drafted the graph as a set of vertices (where the id is the subject of the set of triples and the value is all of its triples) and a set of edges (properties connecting two vertices, this is only possible if the object is an URI). Thus, once computed the subgraph of a Person, if I merge the values of all reachable vertices, I'll obtain all the triples of such a subgraph. On Tue, Apr 14, 2015 at 4:55 PM, Vasiliki Kalavri vasilikikala...@gmail.com wrote: Hi Flavio, I'm not quite familiar with RDF or sparql, so not all of your code is clear to me. Your first TODO is compute subgraph for Person. Is Person a vertex id in your graph? A vertex value? And by subgraph of Person, do you mean all the vertices that can be reached starting from this node and following the graph edges? -Vasia. On 14 April 2015 at 10:37, Flavio Pompermaier pomperma...@okkam.it wrote: Hi to all, I made a simple RDF Gelly test and I shared it on my github repo at https://github.com/fpompermaier/rdf-gelly-test. I basically setup the Gelly stuff but I can't proceed and compute the drafted TODOs. Could someone help me and implementing them..? I think this could become a nice example of how Gelly could help in handling RDF graphs :) Best, Flavio On Mon, Mar 23, 2015 at 10:41 AM, Flavio Pompermaier pomperma...@okkam.it wrote: Thanks Vasiliki, when I'll find the time I'll try to make a quick prototype using the pointers you suggested! Thanks for the support, Flavio On Mon, Mar 23, 2015 at 10:31 AM, Vasiliki Kalavri vasilikikala...@gmail.com wrote: Hi Flavio, I'm not familiar with JSON-LD, but as far as I understand, you want to generate some trees from selected root nodes. Once you have created the Graph as Andra describes above, you can first filter out the edges that are of no interest to you, using filterOnEdges. There is a description of how edge filtering works in the Gelly docs [1]. Then, you could use a vertex-centric iteration and propagate a message from the selected root node to the neighbors recursively, until you have the tree. In the vertex-centric model, you program from the perspective of a vertex in the graph. You basically need to define what each vertex does within each iteration (superstep). In Gelly this boils down to two things: (a) what messages this vertex will send to its neighbors and (b) how a vertex will update its value using the received messages. This is also described in the Gelly docs [2]. Also, take a look at the Gelly library [3]. The library methods are implemented using this model and should give you an idea. In your case, you will probably need to simply propagate one message from the root node and gather the newly discovered neighbors in each superstep. I hope this helps! Let us know if you have further questions! -Vasia. [1]: http://ci.apache.org/projects/flink/flink-docs-master/gelly_guide.html#graph-transformations [2]: http://ci.apache.org/projects/flink/flink-docs-master/gelly_guide.html#vertex-centric-iterations [3]: http://github.com/apache/flink/tree/master/flink-staging/flink-gelly/src/main/java/orgThehveflink/graph/library
Re: Queries regarding RDFs with Flink
Thanks Vasiliki, when I'll find the time I'll try to make a quick prototype using the pointers you suggested! Thanks for the support, Flavio On Mon, Mar 23, 2015 at 10:31 AM, Vasiliki Kalavri vasilikikala...@gmail.com wrote: Hi Flavio, I'm not familiar with JSON-LD, but as far as I understand, you want to generate some trees from selected root nodes. Once you have created the Graph as Andra describes above, you can first filter out the edges that are of no interest to you, using filterOnEdges. There is a description of how edge filtering works in the Gelly docs [1]. Then, you could use a vertex-centric iteration and propagate a message from the selected root node to the neighbors recursively, until you have the tree. In the vertex-centric model, you program from the perspective of a vertex in the graph. You basically need to define what each vertex does within each iteration (superstep). In Gelly this boils down to two things: (a) what messages this vertex will send to its neighbors and (b) how a vertex will update its value using the received messages. This is also described in the Gelly docs [2]. Also, take a look at the Gelly library [3]. The library methods are implemented using this model and should give you an idea. In your case, you will probably need to simply propagate one message from the root node and gather the newly discovered neighbors in each superstep. I hope this helps! Let us know if you have further questions! -Vasia. [1]: http://ci.apache.org/projects/flink/flink-docs-master/gelly_guide.html#graph-transformations [2]: http://ci.apache.org/projects/flink/flink-docs-master/gelly_guide.html#vertex-centric-iterations [3]: http://github.com/apache/flink/tree/master/flink-staging/flink-gelly/src/main/java/orgThehveflink/graph/library
Re: Queries regarding RDFs with Flink
Is there anu example about rdf graph generation based on a skeleton structure? On Mar 22, 2015 12:28 PM, Fabian Hueske fhue...@gmail.com wrote: Hi Flavio, also, Gelly is a superset of Spargel. It provides the same features and much more. Since RDF is graph-structured, Gelly might be a good fit for your use case. Cheers, Fabian
Re: Queries regarding RDFs with Flink
Thanks Andrea for the help!
For graph generation I mean that I'd like to materialize subgraphs of my
overall knowledge starting from some root nodes whose rdf type is of
interest (something similar to what JSON-LD does). Is that clear?
On Mar 22, 2015 1:09 PM, Andra Lungu lungu.an...@gmail.com wrote:
Hi Flavio,
We don't have a specific example for generating RDF graphs using Gelly, but
I will try to drop some lines of code here and hope you will find them
useful.
An RDF statement is formed of Subject - Predicate - Object triples. In Edge
notation, the Subject and the Object will be the source and target vertices
respectively, while the edge value will be the predicate.
This being said, say you have an input plain text file that represents the
edges.
A line would look like this : http://test/Frank, marriedWith,
http://test/Mary
This is internally coded in Flink like a Tuple3. So, to read this edge file
you should have something like this:
private static DataSetEdgeString, String
getEdgesDataSet(ExecutionEnvironment env) {
if (fileOutput) {
return env.readCsvFile(edgesInputPath)
.lineDelimiter(\n)
// the subject, predicate, object
.types(String.class, String.class, String.class)
.map(new MapFunctionTuple3String, String, String,
EdgeString,
String() {
@Override
public EdgeString, String map(Tuple3String, String,
String tuple3) throws Exception {
return new Edge(tuple3.f0, tuple3.f2, tuple3.f1);
}
});
} else {
return getDefaultEdges(env);
}
}
After you have this, in your main method, you just write:
GraphLong, String, String rdfGraph = Graph.fromDataSet(edges, env);
I picked up the conversation later on, not sure if that's what you meant by
graph generation...
Cheers,
Andra
On Sun, Mar 22, 2015 at 12:42 PM, Flavio Pompermaier pomperma...@okkam.it
wrote:
Is there anu example about rdf graph generation based on a skeleton
structure?
On Mar 22, 2015 12:28 PM, Fabian Hueske fhue...@gmail.com wrote:
Hi Flavio,
also, Gelly is a superset of Spargel. It provides the same features and
much more.
Since RDF is graph-structured, Gelly might be a good fit for your use
case.
Cheers, Fabian
Re: Queries regarding RDFs with Flink
Hi Flavio, also, Gelly is a superset of Spargel. It provides the same features and much more. Since RDF is graph-structured, Gelly might be a good fit for your use case. Cheers, Fabian
Re: Queries regarding RDFs with Flink
Hi Flavio,
We don't have a specific example for generating RDF graphs using Gelly, but
I will try to drop some lines of code here and hope you will find them
useful.
An RDF statement is formed of Subject - Predicate - Object triples. In Edge
notation, the Subject and the Object will be the source and target vertices
respectively, while the edge value will be the predicate.
This being said, say you have an input plain text file that represents the
edges.
A line would look like this : http://test/Frank, marriedWith,
http://test/Mary
This is internally coded in Flink like a Tuple3. So, to read this edge file
you should have something like this:
private static DataSetEdgeString, String
getEdgesDataSet(ExecutionEnvironment env) {
if (fileOutput) {
return env.readCsvFile(edgesInputPath)
.lineDelimiter(\n)
// the subject, predicate, object
.types(String.class, String.class, String.class)
.map(new MapFunctionTuple3String, String, String,
EdgeString, String() {
@Override
public EdgeString, String map(Tuple3String, String,
String tuple3) throws Exception {
return new Edge(tuple3.f0, tuple3.f2, tuple3.f1);
}
});
} else {
return getDefaultEdges(env);
}
}
After you have this, in your main method, you just write:
GraphLong, String, String rdfGraph = Graph.fromDataSet(edges, env);
I picked up the conversation later on, not sure if that's what you meant by
graph generation...
Cheers,
Andra
On Sun, Mar 22, 2015 at 12:42 PM, Flavio Pompermaier pomperma...@okkam.it
wrote:
Is there anu example about rdf graph generation based on a skeleton
structure?
On Mar 22, 2015 12:28 PM, Fabian Hueske fhue...@gmail.com wrote:
Hi Flavio,
also, Gelly is a superset of Spargel. It provides the same features and
much more.
Since RDF is graph-structured, Gelly might be a good fit for your use
case.
Cheers, Fabian
Re: Queries regarding RDFs with Flink
(transitive). Flink is fairly good at both types of operations. I would look into the graph examples and the graph API for a start: - Graph examples: https://github.com/apache/flink/tree/master/flink-examples/flink-java-examples/src/main/java/org/apache/flink/examples/java/graph - Graph API: https://github.com/apache/flink/tree/master/flink-staging/flink-gelly/src/main/java/org/apache/flink/graph If you have a more specific question, I can give you better pointers ;-) Stephan On Fri, Feb 27, 2015 at 4:48 PM, santosh_rajaguru sani...@gmail.com wrote: Hello, how can flink be useful for processing the data to RDFs and build the ontology? Regards, Santosh -- View this message in context: http://apache-flink-incubator-mailing-list-archive.1008284.n3.nabble.com/Queries-regarding-RDFs-with-Flink-tp4130.html Sent from the Apache Flink (Incubator) Mailing List archive. mailing list archive at Nabble.com.
Re: Queries regarding RDFs with Flink
.nabble.com/Queries-regarding-RDFs-with-Flink-tp4130.html Sent from the Apache Flink (Incubator) Mailing List archive. mailing list archive at Nabble.com.
Re: Queries regarding RDFs with Flink
I have a nice case of RDF manipulation :) Let's say I have the following RDF triples (Tuple3) in two files or tables: TABLE A: http://test/John, type, Person http://test/John, name, John http://test/John, knows, http://test/Mary http://test/John, knows, http://test/Jerry http://test/Jerry, type, Person http://test/Jerry, name, Jerry http://test/Jerry, knows, http://test/Frank http://test/Mary, type, Person http://test/Mary, name, Mary TABLE B: http://test/Frank, type, Person http://test/Frank, name, Frank http://test/Frank, marriedWith, http://test/Mary What is the best way to build up Person-rooted trees with all node's data properties and some expanded path like 'Person.knows.marriedWith' ? Is it better to use Graph/Gelly APIs, Flink Joins, multiple punctuals get from a Key/value store or what? The expected 4 trees should be: tree 1 (root is John) -- http://test/John, type, Person http://test/John, name, John http://test/John, knows, http://test/Mary http://test/John, knows, http://test/Jerry http://test/Jerry, type, Person http://test/Jerry, name, Jerry http://test/Jerry, knows, http://test/Frank http://test/Mary, type, Person http://test/Mary, name, Mary http://test/Frank, type, Person http://test/Frank, name, Frank http://test/Frank, marriedWith, http://test/Mary tree 2 (root is Jerry) -- http://test/Jerry, type, Person http://test/Jerry, name, Jerry http://test/Jerry, knows, http://test/Frank http://test/Frank, type, Person http://test/Frank, name, Frank http://test/Frank, marriedWith, http://test/Mary http://test/Mary, type, Person http://test/Mary, name, Mary tree 3 (root is Mary) -- http://test/Mary, type, Person http://test/Mary, name, Mary tree 4 (root is Frank) -- http://test/Frank, type, Person http://test/Frank, name, Frank http://test/Frank, marriedWith, http://test/Mary http://test/Mary, type, Person http://test/Mary, name, Mary Thanks in advance, Flavio On Mon, Mar 2, 2015 at 5:04 PM, Stephan Ewen se...@apache.org wrote: Hey Santosh! RDF processing often involves either joins, or graph-query like operations (transitive). Flink is fairly good at both types of operations. I would look into the graph examples and the graph API for a start: - Graph examples: https://github.com/apache/flink/tree/master/flink-examples/flink-java-examples/src/main/java/org/apache/flink/examples/java/graph - Graph API: https://github.com/apache/flink/tree/master/flink-staging/flink-gelly/src/main/java/org/apache/flink/graph If you have a more specific question, I can give you better pointers ;-) Stephan On Fri, Feb 27, 2015 at 4:48 PM, santosh_rajaguru sani...@gmail.com wrote: Hello, how can flink be useful for processing the data to RDFs and build the ontology? Regards, Santosh -- View this message in context: http://apache-flink-incubator-mailing-list-archive.1008284.n3.nabble.com/Queries-regarding-RDFs-with-Flink-tp4130.html Sent from the Apache Flink (Incubator) Mailing List archive. mailing list archive at Nabble.com.
Re: Queries regarding RDFs with Flink
Hi Flavio, if you want to use Gelly to model your data as a graph, you can load your Tuple3s as Edges. This will result in http://test/John;, Person, Frank, etc to be vertices and type, name, knows to be edge values. In the first case, you can use filterOnEdges() to get the subgraph with the relation edges. Once you have the graph, you could probably use a vertex-centric iteration to generate the trees. It seems to me that you need something like a BFS from each vertex. Keep in mind that this can be a very costly operation in terms of memory and communication for large graphs. Let me know if you have any questions! Cheers, V. On 3 March 2015 at 09:13, Flavio Pompermaier pomperma...@okkam.it wrote: I have a nice case of RDF manipulation :) Let's say I have the following RDF triples (Tuple3) in two files or tables: TABLE A: http://test/John, type, Person http://test/John, name, John http://test/John, knows, http://test/Mary http://test/John, knows, http://test/Jerry http://test/Jerry, type, Person http://test/Jerry, name, Jerry http://test/Jerry, knows, http://test/Frank http://test/Mary, type, Person http://test/Mary, name, Mary TABLE B: http://test/Frank, type, Person http://test/Frank, name, Frank http://test/Frank, marriedWith, http://test/Mary What is the best way to build up Person-rooted trees with all node's data properties and some expanded path like 'Person.knows.marriedWith' ? Is it better to use Graph/Gelly APIs, Flink Joins, multiple punctuals get from a Key/value store or what? The expected 4 trees should be: tree 1 (root is John) -- http://test/John, type, Person http://test/John, name, John http://test/John, knows, http://test/Mary http://test/John, knows, http://test/Jerry http://test/Jerry, type, Person http://test/Jerry, name, Jerry http://test/Jerry, knows, http://test/Frank http://test/Mary, type, Person http://test/Mary, name, Mary http://test/Frank, type, Person http://test/Frank, name, Frank http://test/Frank, marriedWith, http://test/Mary tree 2 (root is Jerry) -- http://test/Jerry, type, Person http://test/Jerry, name, Jerry http://test/Jerry, knows, http://test/Frank http://test/Frank, type, Person http://test/Frank, name, Frank http://test/Frank, marriedWith, http://test/Mary http://test/Mary, type, Person http://test/Mary, name, Mary tree 3 (root is Mary) -- http://test/Mary, type, Person http://test/Mary, name, Mary tree 4 (root is Frank) -- http://test/Frank, type, Person http://test/Frank, name, Frank http://test/Frank, marriedWith, http://test/Mary http://test/Mary, type, Person http://test/Mary, name, Mary Thanks in advance, Flavio On Mon, Mar 2, 2015 at 5:04 PM, Stephan Ewen se...@apache.org wrote: Hey Santosh! RDF processing often involves either joins, or graph-query like operations (transitive). Flink is fairly good at both types of operations. I would look into the graph examples and the graph API for a start: - Graph examples: https://github.com/apache/flink/tree/master/flink-examples/flink-java-examples/src/main/java/org/apache/flink/examples/java/graph - Graph API: https://github.com/apache/flink/tree/master/flink-staging/flink-gelly/src/main/java/org/apache/flink/graph If you have a more specific question, I can give you better pointers ;-) Stephan On Fri, Feb 27, 2015 at 4:48 PM, santosh_rajaguru sani...@gmail.com wrote: Hello, how can flink be useful for processing the data to RDFs and build the ontology? Regards, Santosh -- View this message in context: http://apache-flink-incubator-mailing-list-archive.1008284.n3.nabble.com/Queries-regarding-RDFs-with-Flink-tp4130.html Sent from the Apache Flink (Incubator) Mailing List archive. mailing list archive at Nabble.com.
Re: Queries regarding RDFs with Flink
Hey Santosh! RDF processing often involves either joins, or graph-query like operations (transitive). Flink is fairly good at both types of operations. I would look into the graph examples and the graph API for a start: - Graph examples: https://github.com/apache/flink/tree/master/flink-examples/flink-java-examples/src/main/java/org/apache/flink/examples/java/graph - Graph API: https://github.com/apache/flink/tree/master/flink-staging/flink-gelly/src/main/java/org/apache/flink/graph If you have a more specific question, I can give you better pointers ;-) Stephan On Fri, Feb 27, 2015 at 4:48 PM, santosh_rajaguru sani...@gmail.com wrote: Hello, how can flink be useful for processing the data to RDFs and build the ontology? Regards, Santosh -- View this message in context: http://apache-flink-incubator-mailing-list-archive.1008284.n3.nabble.com/Queries-regarding-RDFs-with-Flink-tp4130.html Sent from the Apache Flink (Incubator) Mailing List archive. mailing list archive at Nabble.com.
Re: Queries regarding RDFs with Flink
Hi Santosh, I'm not aware of any existing tools in Flink to process RDFs. However, Flink should be useful for processing such data. You can probably use an existing RDF parser for Java to get the data into the system. Best, Robert On Fri, Feb 27, 2015 at 4:48 PM, santosh_rajaguru sani...@gmail.com wrote: Hello, how can flink be useful for processing the data to RDFs and build the ontology? Regards, Santosh -- View this message in context: http://apache-flink-incubator-mailing-list-archive.1008284.n3.nabble.com/Queries-regarding-RDFs-with-Flink-tp4130.html Sent from the Apache Flink (Incubator) Mailing List archive. mailing list archive at Nabble.com.
