5 Using the In-Memory Analyst

1. Open a terminal session on the system where property graph support is installed.
2. Either start a local (embedded) in-memory analyst instance or connect to a remote in-memory analyst instance
   • Java example of starting a local (embedded) instance:

     import java.util.Map;
     import java.util.HashMap;
     import oracle.pgx.api.*;
     import oracle.pgx.config.PgxConfig.Field;
      
     String url = Pgx.EMBEDDED_URL; // local JVM
     ServerInstance instance = Pgx.getInstance(url);
     instance.startEngine(); // will use default configuration
     PgxSession session = instance.createSession("test");
     

   • Java example of connecting to a remote instance:

     import java.util.Map;
     import java.util.HashMap;
     import oracle.pgx.api.*;
     import oracle.pgx.config.PgxConfig.Field;
      
     String url = "http://my-server.com:8080/pgx" // replace with base URL of your setup
     ServerInstance instance = Pgx.getInstance(url);
     PgxSession session = instance.createSession("test");
     

3. In the shell, enter the following commands, but select only one of the commands to start or connect to the desired type of instance:

   cd $PGX_HOME
   ./bin/pgx --help
   ./bin/pgx --version
    
   # start embedded shell
   ./bin/pgx
    
   # start remote shell
   ./bin/pgx --base_url http://my-server.com:8080/pgx
   

   For the embedded shell, the output should be similar to the following:

   10:43:46,666 [main] INFO Ctrl$2 - >>> PGX engine running.
   pgx>
   

4. Optionally, show the predefined variables:

   pgx> instance
   ==> PGX Server Instance running on embedded mode
   pgx> session
   ==> PGX session pgxShell registered at PGX Server Instance running on embedded mode
   pgx> analyst
   ==> Analyst for PGX session pgxShell registered at PGX Server Instance running on embedded mode
   pgx>
   

   Examples in some other topics assume that the instance and session variables have been set as shown here.

The in-memory analyst shell provides a help system, which you access using the :help command.

An example graph is included in the installation directory, under /opt/oracle/oracle-spatial-graph/property_graph/examples/pgx/graphs/. It uses a configuration file that describes how the in-memory analyst reads the graph.

pgx> cat /opt/oracle/oracle-spatial-graph/property_graph/examples/pgx/graphs/sample.adj.json 
===> {
  "uri": "sample.adj", 
  "format": "adj_list",
  "node_props": [{ 
    "name": "prop", 
    "type": "integer" 
  }],
  "edge_props": [{ 
    "name": "cost", 
    "type": "double" 
  }],
  "separator": " "
}

The uri field provides the location of the graph data. This path resolves relative to the parent directory of the configuration file. When the in-memory analyst loads the graph, it searches the examples/graphs directory for a file named sample.adj.

The other fields indicate that the graph data is provided in adjacency list format, and consists of one node property of type integer and one edge property of type double.

This is the graph data in adjacency list format:

pgx> cat /opt/oracle/oracle-spatial-graph/property_graph/examples/pgx/graphs/sample.adj
===> 128 10 1908 27.03 99 8.51 
99 2 333 338.0
1908 889
333 6 128 51.09

Figure 5-1 shows a property graph created from the data:

Figure 5-1 Property Graph Rendered by sample.adj Data

Description of "Figure 5-1 Property Graph Rendered by sample.adj Data"

To read a graph into memory, you must pass the following information:

• The path to the graph configuration file that specifies the graph metadata

• A unique alphanumeric name that you can use to reference the graph

  An error results if you previously loaded a different graph with the same name.

Example: Using the Shell to Read a Graph

pgx> graph = session.readGraphWithProperties("/opt/oracle/oracle-spatial-graph/property_graph/examples/pgx/graphs/sample.adj.json", "sample");
==> PGX Graph named sample bound to PGX session pgxShell ...
pgx> graph.getNumVertices()
==> 4

Example: Using Java to Read a Graph

import oracle.pgx.api.*;
 
PgxGraph graph = session.readGraphWithProperties("/opt/oracle/oracle-spatial-graph/property_graph/examples/pgx/graphs/sample.adj.json");

The following topics contain additional examples of reading a property graph into memory:

• Read a Graph Stored in Apache HBase into Memory

• Read a Graph Stored in Oracle NoSQL Database into Memory

• Read a Graph Stored in the Local File System into Memory

This example creates a small, simple graph in adjacency list format with no vertex or edge properties. Each line contains the vertex (node) ID, followed by the vertex IDs to which iits outgoing edges point:

1 2
2 3 4
3 4
4 2

In this list, a single space separates the individual tokens. The in-memory analyst supports other separators, which you can specify in the graph configuration file.

Figure 5-2 shows the data rendered as a property graph with 4 vertices and 5 edges. The edge from vertex 2 to vertex 4 points in both directions.

Figure 5-2 Simple Custom Property Graph

Description of "Figure 5-2 Simple Custom Property Graph"

Reading a graph into the in-memory analyst requires a graph configuration. You can provide the graph configuration using either of these methods:

• Write the configuration settings in JSON format into a file

• Using a Java GraphConfigBuilder object.

This example shows both methods.

{
    "uri": "graph.adj",
    "format":"adj_list",
    "separator":" "
}

import oracle.pgx.config.FileGraphConfig;
import oracle.pgx.config.Format;
import oracle.pgx.config.GraphConfigBuilder;
FileGraphConfig config = GraphConfigBuilder 
   .forFileFormat(Format.ADJ_LIST) 
   .setUri("graph.adj") 
   .setSeparator(" ") 
   .build();

The graph in "Creating a Simple Graph File" consists of vertices and edges, without vertex or edge properties. Vertex properties are positioned directly after the source vertex ID in each line. The graph data looks like this after a double vertex (node) property is added to the graph:

1 0.1 2
2 2.0 3 4
3 0.3 4
4 4.56789 2

For the in-memory analyst to read the modified data file, you must add a vertex node) property in the configuration file or the builder code. The following examples provide a descriptive name for the property and set the type to double.

{
    "uri": "graph.adj",
    "format":"adj_list",
    "separator":" ",
    "node_props":[{
        "name":"double-prop",
        "type":"double"
    }]
}

import oracle.pgx.common.types.PropertyType;
import oracle.pgx.config.FileGraphConfig;
import oracle.pgx.config.Format;
import oracle.pgx.config.GraphConfigBuilder;

FileGraphConfig config = GraphConfigBuilder.forFileFormat(Format.ADJ_LIST) 
    .setUri("graph.adj") 
    .setSeparator(" ") 
    .addNodeProperty("double-prop", PropertyType.DOUBLE) 
    .build();

The previous examples used integer vertex (node) IDs. The default in In-Memory Analytics is integer vertex IDs, but you can define a graph to use string vertex IDs instead.

This data file uses "node 1", "node 2", and so forth instead of just the digit:

"node 1" 0.1 "node 2"
"node 2" 2.0 "node 3" "node 4"
"node 3" 0.3 "node 4"
"node 4" 4.56789 "node 2"

Again, you must modify the graph configuration to match the data file:

{
    "uri": "graph.adj",
    "format":"adj_list",
    "separator":" ",
    "node_props":[{
        "name":"double-prop",
        "type":"double"
    }],
    "node_id_type":"string"
}

import oracle.pgx.common.types.IdType;
import oracle.pgx.common.types.PropertyType;
import oracle.pgx.config.FileGraphConfig;
import oracle.pgx.config.Format;
import oracle.pgx.config.GraphConfigBuilder;

FileGraphConfig config = GraphConfigBuilder.forFileFormat(Format.ADJ_LIST) 
    .setUri("graph.adj") 
    .setSeparator(" ") 
    .addNodeProperty("double-prop", PropertyType.DOUBLE) 
    .setNodeIdType(IdType.STRING) 
    .build();

This example adds an edge property of type string to the graph. The edge properties are positioned after the destination vertex (node) ID.

"node1" 0.1 "node2" "edge_prop_1_2"
"node2" 2.0 "node3" "edge_prop_2_3" "node4" "edge_prop_2_4"
"node3" 0.3 "node4" "edge_prop_3_4"
"node4" 4.56789 "node2" "edge_prop_4_2"

The graph configuration must match the data file:

{
    "uri": "graph.adj",
    "format":"adj_list",
    "separator":" ",
    "node_props":[{
        "name":"double-prop",
        "type":"double"
    }],
    "node_id_type":"string",
     "edge_props":[{
        "name":"edge-prop",
        "type":"string"
    }]
}

import oracle.pgx.common.types.IdType;
import oracle.pgx.common.types.PropertyType;
import oracle.pgx.config.FileGraphConfig;
import oracle.pgx.config.Format;
import oracle.pgx.config.GraphConfigBuilder;

FileGraphConfig config = GraphConfigBuilder.forFileFormat(Format.ADJ_LIST) 
    .setUri("graph.adj") 
    .setSeparator(" ") 
    .addNodeProperty("double-prop", PropertyType.DOUBLE) 
    .setNodeIdType(IdType.STRING) 
    .addEdgeProperty("edge-prop", PropertyType.STRING) 
    .build();

This example reads a graph into memory and analyzes it using the Pagerank algorithm. This analysis creates a new vertex property to store the PageRank values.

pgx> g = session.readGraphWithProperties("/opt/oracle/oracle-spatial-graph/property_graph/examples/pgx/graphs/sample.adj.json", "my-graph")
==> ...
pgx> rank = analyst.pagerank(g, 0.001, 0.85, 100)

PgxGraph g = session.readGraphWithProperties("/opt/oracle/oracle-spatial-graph/property_graph/examples/pgx/graphs/sample.adj.json", "my-graph");
VertexProperty<Integer, Double> rank = session.createAnalyst().pagerank(g, 0.001, 0.85, 100);

This example stores the graph, the result of the Pagerank analysis, and all original edge properties as a file in edge-list format on disk.

To store a graph, you must specify:

• The graph format

• A path where the file will be stored

• The properties to be stored. Specify VertexProperty.ALL or EdgeProperty.ALL to store all properties, or VertexProperty.NONE or EdgePropery.NONE to store no properties. To specify individual properties, pass in the VertexProperty or /EdgeProperty objects you want to store.

• A flag that indicates whether to overwrite an existing file with the same name

The following examples store the graph data in /tmp/sample_pagerank.elist, with the /tmp/sample_pagerank.elist.json configuration file. The return value is the graph configuration stored in the file. You can use it to read the graph again.

pgx> config = g.store(Format.EDGE_LIST, "/tmp/sample_pagerank.elist", [rank], EdgeProperty.ALL, false)
==> {"node_props":[{"name":"session-12kta9mj-vertex-prop-double-2","type":"double"}],"error_handling":{},"node_id_type":"integer","uri":"/tmp/g.edge","loading":{},"edge_props":[{"name":"cost","type":"double"}],"format":"edge_list"}

import oracle.pgx.api.*;
import oracle.pgx.config.*;
 
FileGraphConfig config = g.store(Format.EDGE_LIST, "/tmp/sample_pagerank.elist", Collections.singletonList(rank), EdgeProperty.ALL, false);

The in-memory analyst contains a set of built-in algorithms that are available as Java APIs. The details of the APIs are documented in the Javadoc that in included in the product documentation library. Specifically, see the BuiltinAlgorithms interface Method Summary for a list of the supported in-memory analyst methods.

For example, this is the Pagerank procedure signature:

/**
   * Classic pagerank algorithm. Time complexity: O(E * K) with E = number of edges, K is a given constant (max
   * iterations)
   *
   * @param graph
   *          graph
   * @param e
   *          maximum error for terminating the iteration
   * @param d
   *          damping factor
   * @param max
   *          maximum number of iterations
   * @return Vertex Property holding the result as a double
   */
  public <ID extends Comparable<ID>> VertexProperty<ID, Double> pagerank(PgxGraph graph, double e, double d, int max);

For triangle counting, the sortByDegree boolean parameter of countTriangles() allows you to control whether the graph should first be sorted by degree (true) or not (false). If true, more memory will be used, but the algorithm will run faster; however, if your graph is very large, you might want to turn this optimization off to avoid running out of memory.

pgx> analyst.countTriangles(graph, true)
==> 1

import oracle.pgx.api.*;
 
Analyst analyst = session.createAnalyst();
long triangles = analyst.countTriangles(graph, true);

Pagerank computes a rank value between 0 and 1 for each vertex (node) in the graph and stores the values in a double property. The algorithm therefore creates a vertex property of type double for the output.

In the in-memory analyst, there are two types of vertex and edge properties:

• Persistent Properties: Properties that are loaded with the graph from a data source are fixed, in-memory copies of the data on disk, and are therefore persistent. Persistent properties are read-only, immutable and shared between sessions.

• Transient Properties: Values can only be written to transient properties, which are session private. You can create transient properties by alling createVertexProperty and createEdgeProperty() on PgxGraph objects.

This example obtains the top three vertices with the highest Pagerank values. It uses a transient vertex property of type double to hold the computed Pagerank values. The Pagerank algorithm uses a maximum error of 0.001, a damping factor of 0.85, and a maximum number of 100 iterations.

pgx> rank = analyst.pagerank(graph, 0.001, 0.85, 100);
==> ...
pgx> rank.getTopKValues(3)
==> 128=0.1402019732468347
==> 333=0.12002296283541904
==> 99=0.09708583862990475

import java.util.Map.Entry;
import oracle.pgx.api.*;
 
Analyst analyst = session.createAnalyst();
VertexProperty<Integer, Double> rank = analyst.pagerank(graph, 0.001, 0.85, 100);
for (Entry<Integer, Double> entry : rank.getTopKValues(3)) {
 System.out.println(entry.getKey() + "=" entry.getValue());
}

Filter expressions are expressions that are evaluated for each edge. The expression can define predicates that an edge must fulfil to be contained in the result, in this case a subgraph.

Consider the graph in Figure 5-1, which consists of four vertices (nodes) and four edges. For an edge to match the filter expression src.prop == 10, the source vertex prop property must equal 10. Two edges match that filter expression, as shown in Figure 5-3.

Figure 5-3 Edges Matching src.prop == 10

Description of "Figure 5-3 Edges Matching src.prop == 10"

Figure 5-4 shows the graph that results when the filter is applied. The filter excludes the edges associated with vertex 333, and the vertex itself.

Figure 5-4 Graph Created by the Simple Filter

Description of "Figure 5-4 Graph Created by the Simple Filter"

Using filter expressions to select a single vertex or a set of vertices is difficult. For example, selecting only the vertex with the property value 10 is impossible, because the only way to match the vertex is to match an edge where 10 is either the source or destination property value. However, when you match an edge you automatically include the source vertex, destination vertex, and the edge itself in the result.

The following examples create the subgraph described in "About Filter Expressions".

subgraph = graph.filter(new VertexFilter("vertex.prop == 10"))

import oracle.pgx.api.*;
import oracle.pgx.api.filter.*;

PgxGraph graph = session.readGraphWithProperties(...);
PgxGraph subgraph = graph.filter(new VertexFilter("vertex.prop == 10"));

This example uses a slightly more complex filter. It uses the outDegree function, which calculates the number of outgoing edges for an identifier (source src or destination dst). The following filter expression matches all edges with a cost property value greater than 50 and a destination vertex (node) with an outDegree greater than 1.

dst.outDegree() > 1 && edge.cost > 50

One edge in the sample graph matches this filter expression, as shown in Figure 5-5.

Figure 5-5 Edges Matching the outDegree Filter

Description of "Figure 5-5 Edges Matching the outDegree Filter"

Figure 5-6 shows the graph that results when the filter is applied. The filter excludes the edges associated with vertixes 99 and 1908, and so excludes those vertices also.

Figure 5-6 Graph Created by the outDegree Filter

Description of "Figure 5-6 Graph Created by the outDegree Filter"

You can create a bipartite subgraph by specifying a set of vertices (nodes), which are used as the left side. A bipartite subgraph has edges only between the left set of vertices and the right set of vertices. There are no edges within those sets, such as between two nodes on the left side. In the in-memory analyst, vertices that are isolated because all incoming and outgoing edges were deleted are not part of the bipartite subgraph.

The following figure shows a bipartite subgraph. No properties are shown.

Description of the illustration GUID-CE62AAFC-0A54-4565-BE64-8E6DE26E46EA-default.png

The following examples create a bipartite subgraph from the simple graph created in Figure 5-1. They create a vertex collection and fill it with the vertices for the left side.

pgx> s = graph.createVertexSet()
==> ...
pgx> s.addAll([graph.getVertex(333), graph.getVertex(99)])
==> ...
pgx> s.size()
==> 2
pgx> bGraph = graph.bipartiteSubGraphFromLeftSet(s)
==> PGX Bipartite Graph named sample-sub-graph-4

import oracle.pgx.api.*;
 
VertexSet<Integer> s = graph.createVertexSet();
s.addAll(graph.getVertex(333), graph.getVertex(99));
BipartiteGraph bGraph = graph.bipartiteSubGraphFromLeftSet(s);

When you create a subgraph, the in-memory analyst automatically creates a Boolean vertex (node) property that indicates whether the vertex is on the left side. You can specify a unique name for the property.

The resulting bipartite subgraph looks like this:

Description of the illustration GUID-43F3394A-1159-4F90-BFED-7EC83364E3D3-default.png

Vertex 1908 is excluded from the bipartite subgraph. The only edge that connected that vertex extended from 128 to 1908. The edge was removed, because it violated the bipartite properties of the subgraph. Vertex 1908 had no other edges, and so was removed also.

The in-memory analyst web deployment uses BASIC Auth by default. You should change to a more secure authentication mechanism for a production deployment.

To change the authentication mechanism, modify the security-constraint element of the web.xml deployment descriptor in the web application archive (WAR) file.

To download and install the latest version of Oracle WebLogic Server, see

http://www.oracle.com/technetwork/middleware/weblogic/documentation/index.html

To deploy the in-memory analyst to Oracle WebLogic, use commands like the following. Substitute your administrative credentials and WAR file for the values shown in this example:

cd $MW_HOME/user_projects/domains/mydomain
. bin/setDomainEnv.sh
java weblogic.Deployer -adminurl http://localhost:7001 -username username -password password -deploy -upload $PGX_HOME/lib/server/pgx-webapp-0.9.0.war

If the script runs successfully, you will see a message like this one:

Target state: deploy completed on Server myserver

Verify that you can connect to the server:

$PGX_HOME/bin/pgx --base_url scott:tiger123@localhost:7001/pgx

The simplest way to connect to an in-memory analyst instance is to specify the base URL of the server. The following base URL can connect the SCOTT user to the local instance listening on port 8080:

http://scott:tiger@localhost:8080/pgx

To start the in-memory analyst shell with this base URL, you use the --base_url command line argument

cd $PGX_HOME
./bin/pgx --base_url http://scott:tiger@localhost:8080/pgx

You can connect to a remote instance the same way. However, the in-memory analyst currently does not provide remote support for the Control API.

You can specify the base URL when you initialize the in-memory analyst using Java. An example is as follows. A URL to an in-memory analyst server is provided to the getInMemAnalyst API call.

import oracle.pg.nosql.*;
import oracle.pgx.api.*;
 
PgNosqlGraphConfig cfg = GraphConfigBuilder.forNosql().setName("mygraph").setHosts(...).build();
OraclePropertyGraph opg = OraclePropertyGraph.getInstance(cfg);
ServerInstance remoteInstance = Pgx.getInstance("http://scott:tiger@hostname:port/pgx");
PgxSession session = remoteInstance.createSession("my-session");
 
PgxGraph graph = session.readGraphWithProperties(opg.getConfig());

The in-memory analyst shell uses HTTP requests to communicate with the in-memory analyst server. You can use the same HTTP endpoints directly or use them to write your own client library.

This example uses HTTP to call create session:

HTTP POST 'http://scott:tiger@localhost:8080/pgx/core/session' with payload '{"source":"shell"}'
Response: {"sessionId":"session-shell-42v3b9n7"}

The call to create session returns a session identifier. Most HTTP calls return an in-memory analyst UUID, which identifies the resource that holds the result of the request. Many in-memory analyst requests take a while to complete, but you can obtain a handle to the result immediately. Using that handle, an HTTP GET call to a special endpoint provides the result of the request (or block, if the request is not complete).

Most interactions with the in-memory analyst with HTTP look like this example:

// any request, with some payload
HTTP POST 'http://scott:tiger@localhost:8080/pgx/core/session/session-shell-42v3b9n7/graph' with payload '{"graphName":"sample","graphConfig":{"edge_props":[{"type":"double","name":"cost"}],"format":"adj_list","separator":" ","node_props":[{"type":"integer","name":"prop"}],"uri":"http://path.to.some.server/pgx/sample.adj"}}'
Response: {"futureId":"15fc72e9-42e9-4527-9a31-bd20eb0adafb"}

// get the result using the in-memory analyst future UUID.
HTTP GET 'http://scott:tiger@localhost:8080/pgx/future/session/session-shell-42v3b9n7/result/15fc72e9-42e9-4527-9a31-bd20eb0adafb'
Response: {"stats":{"loadingTimeMillis":0,"estimatedMemoryMegabytes":0,"numNodes":4,"numEdges":4},"graphName":"sample","nodeProperties":{"prop":"integer"},"edgeProperties":{"cost":"double"}}

This example copies the sample.adj graph data and its configuration file into HDFS, and then loads it into memory.

1. Copy the graph data into HDFS:

   cd $PGX_HOME
   hadoop fs -mkdir -p /user/pgx
   hadoop fs -copyFromLocal examples/graphs/sample.adj /user/pgx
   

2. Edit the uri field of the graph configuration file to point to an HDFS resource:

   {
     "uri": "hdfs:/user/pgx/sample.adj", 
     "format": "adj_list",
     "node_props": [{ 
       "name": "prop", 
       "type": "integer" 
     }],
     "edge_props": [{ 
       "name": "cost", 
       "type": "double" 
     }],
     "separator": " "
   }
   

3. Copy the configuration file into HDFS:

   cd $PGX_HOME
   hadoop fs -copyFromLocal examples/graphs/sample.adj.json /user/pgx
   

4. Load the sample graph from HDFS into the in-memory analyst, as shown in the following examples.

g = session.readGraphWithProperties("hdfs:/user/pgx/sample.adj.json");
===> {
  "graphName" : "G",
  "nodeProperties" : {
    "prop" : "integer"
  },
  "edgeProperties" : {
    "cost" : "double"
  },
  "stats" : {
    "loadingTimeMillis" : 628,
    "estimatedMemoryMegabytes" : 0,
    "numNodes" : 4,
    "numEdges" : 4
  }
}

import oracle.pgx.api.*;
PgxGraph g = session.readGraphWithProperties("hdfs:/user/pgx/sample.adj.json");

The in-memory analyst binary format (.pgb) is a proprietary binary graph format for the in-memory analyst. Fundamentally, a .pgb file is a binary dump of a graph and its property data, and it is efficient for in-memory analyst operations. You can use this format to quickly serialize a graph snapshot to disk and later read it back into memory.

You should not alter an existing .pgb file.

The following examples store the sample graph, currently in memory, in PGB format in HDFS.

g.store(Format.PGB, "hdfs:/user/pgx/sample.pgb", VertexProperty.ALL, EdgeProperty.ALL, true)

import oracle.pgx.config.GraphConfig;
import oracle.pgx.api.*;
 
GraphConfig pgbGraphConfig = g.store(Format.PGB, "hdfs:/user/pgx/sample.pgb", VertexProperty.ALL, EdgeProperty.ALL, true);

hadoop fs -ls /user/pgx

The following is the HdfsExample Java class for the previous examples:

import oracle.pgx.api.Pgx;
import oracle.pgx.api.PgxGraph;
import oracle.pgx.api.PgxSession;
import oracle.pgx.api.ServerInstance;
import oracle.pgx.config.Format;
import oracle.pgx.config.GraphConfig;
import oracle.pgx.config.GraphConfigFactory;
 
public class HdfsDemo {
  public static void main(String[] mainArgs) throws Exception {
    ServerInstance instance = Pgx.getInstance(Pgx.EMBEDDED_URL);
    instance.startEngine();
    PgxSession session = Pgx.createSession("my-session");
    GraphConfig adjConfig = GraphConfigFactory.forAnyFormat().fromHdfs("/user/pgx/sample.adj.json");
    PgxGraph graph1 = session.readGraphWithProperties(adjConfig);
    GraphConfig pgbConfig = graph1.store(Format.PGB, "hdfs:/user/pgx/sample.pgb");
    PgxGraph graph2 = session.readGraphWithProperties(pgbConfig);
    System.out.println("graph1 N = " + graph1.getNumVertices() + " E = " + graph1.getNumEdges());
    System.out.println("graph2 N = " + graph1.getNumVertices() + " E = " + graph2.getNumEdges());
  }
}

These commands compile the HdfsExample class:

cd $PGX_HOME
mkdir classes
javac -cp ../lib/* HdfsDemo.java -d classes

This command runs the HdfsExample class:

java -cp ../lib/*:conf:classes:$HADOOP_CONF_DIR HdfsDemo

Before you can start the in-memory analyst as a YARN application, you must configure the in-memory analyst YARN client.

You can connect to in-memory analyst services in YARN the same way you connect to any in-memory analyst server. For example, to connect the Shell interface with the in-memory analyst service, use a command like this one:

$PGX_HOME/bin/pgx --base_url username:password@hostname:port

In this syntax, username and password match those specified in the YARN configuration.

To monitor in-memory analyst services, click the corresponding YARN application in the Resource Manager Web UI. By default, the Web UI is located at

http://resource-manager-hostname:8088/cluster