--- /dev/null
+/**
+ * ============LICENSE_START===================================================
+ * SPARKY (AAI UI service)
+ * ============================================================================
+ * Copyright © 2017 AT&T Intellectual Property.
+ * Copyright © 2017 Amdocs
+ * All rights reserved.
+ * ============================================================================
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * ============LICENSE_END=====================================================
+ *
+ * ECOMP and OpenECOMP are trademarks
+ * and service marks of AT&T Intellectual Property.
+ */
+package org.onap.aai.sparky.viewandinspect.services;
+
+import java.io.File;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.List;
+import java.util.Map;
+import java.util.UUID;
+
+import org.onap.aai.cl.api.Logger;
+import org.onap.aai.cl.eelf.LoggerFactory;
+import org.onap.aai.sparky.config.SparkyResourceLoader;
+import org.onap.aai.sparky.logging.AaiUiMsgs;
+import org.onap.aai.sparky.subscription.config.SubscriptionConfig;
+import org.onap.aai.sparky.util.ConfigHelper;
+import org.onap.aai.sparky.viewandinspect.config.VisualizationConfigs;
+import org.onap.aai.sparky.viewandinspect.entity.ActiveInventoryNode;
+import org.onap.aai.sparky.viewandinspect.entity.D3VisualizationOutput;
+import org.onap.aai.sparky.viewandinspect.entity.GraphMeta;
+import org.onap.aai.sparky.viewandinspect.entity.NodeDebug;
+import org.onap.aai.sparky.viewandinspect.entity.SparkyGraphLink;
+import org.onap.aai.sparky.viewandinspect.entity.SparkyGraphNode;
+
+import com.fasterxml.jackson.core.JsonProcessingException;
+import com.fasterxml.jackson.databind.ObjectMapper;
+import com.fasterxml.jackson.databind.ObjectWriter;
+
+/**
+ * The idea here is to receive a collection of graphs and then fold them together (or not) based on
+ * configuration. The first goal will be to fold all like-resources together, but the choice of
+ * folding could/should be configurable, and will simply change the degree of link based nodes when
+ * we generate the Node-Array and Link-Array output.
+ *
+ * @author DAVEA
+ *
+ */
+
+public class VisualizationTransformer {
+
+ private static final Logger LOG = LoggerFactory.getInstance().getLogger(
+ VisualizationTransformer.class);
+
+ List<SparkyGraphNode> flatNodeArray = new ArrayList<SparkyGraphNode>();
+
+ /*
+ * Maybe this isn't a string but Json-Model objects that we will convert to final string
+ * representation when we dump the node-array and link-array collections the post-data blob in the
+ * HttpServletResponse.
+ */
+
+ List<SparkyGraphLink> linkArrayOutput = new ArrayList<SparkyGraphLink>();
+
+ private VisualizationConfigs visualizationConfigs;
+ private SubscriptionConfig subConfig;
+
+ /**
+ * Instantiates a new visualization transformer.
+ *
+ * @throws Exception the exception
+ */
+ public VisualizationTransformer(VisualizationConfigs visualizationConfigs,
+ SubscriptionConfig subConfig) throws Exception {
+ this.visualizationConfigs = visualizationConfigs;
+ this.subConfig = subConfig;
+ }
+
+
+ /**
+ * Log optime.
+ *
+ * @param method the method
+ * @param startTimeInMs the start time in ms
+ */
+ private void logOptime(String method, long startTimeInMs) {
+ LOG.info(AaiUiMsgs.OPERATION_TIME, method,
+ String.valueOf((System.currentTimeMillis() - startTimeInMs)));
+ }
+
+ /**
+ * Adds the search target attributes to root node.
+ */
+ public void addSearchTargetAttributesToRootNode() {
+
+ for (SparkyGraphNode n : flatNodeArray) {
+ if (n.isRootNode()) {
+ n.getNodeMeta().setSearchTarget(true);
+ n.getNodeMeta().setClassName(this.visualizationConfigs.getSelectedSearchedNodeClassName());
+ }
+
+ }
+
+ }
+
+ /**
+ * Generate visualization output.
+ *
+ * @param preProcessingOpTimeInMs the pre processing op time in ms
+ * @param graphMeta the graph meta
+ * @return the d 3 visualization output
+ * @throws JsonProcessingException the json processing exception
+ * @throws IOException Signals that an I/O exception has occurred.
+ */
+
+ public D3VisualizationOutput generateVisualizationOutput(long preProcessingOpTimeInMs,
+ GraphMeta graphMeta) throws JsonProcessingException, IOException {
+
+ long opStartTimeInMs = System.currentTimeMillis();
+
+ /*
+ * iterate over the flat collection, and only add the graph nodes to the graph node collection
+ */
+
+ D3VisualizationOutput output = new D3VisualizationOutput();
+
+ output.setGraphMeta(graphMeta);
+
+ for (SparkyGraphNode n : flatNodeArray) {
+ if ( n.getItemType()!= null) {
+ output.pegCounter(n.getItemType());
+ }
+ }
+
+ output.addNodes(flatNodeArray);
+ output.addLinks(linkArrayOutput);
+
+ int numNodes = flatNodeArray.size();
+ int numLinks = linkArrayOutput.size();
+
+ LOG.info(AaiUiMsgs.VISUALIZATION_GRAPH_OUTPUT, String.valueOf(numNodes),
+ String.valueOf(numLinks));
+
+ if (numLinks < (numNodes - 1)) {
+ LOG.warn(AaiUiMsgs.DANGLING_NODE_WARNING, String.valueOf(numLinks),
+ String.valueOf(numNodes));
+ }
+
+ ObjectMapper mapper = new ObjectMapper();
+
+ SparkyResourceLoader resourceLoader = visualizationConfigs.getResourceLoader();
+ File aaiEntityDescriptorsFile = resourceLoader.getResourceAsFile(visualizationConfigs.getAaiEntityNodeDescriptors(), true);
+
+ if (aaiEntityDescriptorsFile != null) {
+ com.fasterxml.jackson.databind.JsonNode aaiEntityNodeDefinitions =
+ mapper.readTree(aaiEntityDescriptorsFile);
+ graphMeta.setAaiEntityNodeDescriptors(aaiEntityNodeDefinitions);
+ } else {
+ LOG.error(AaiUiMsgs.ERROR_GENERIC, "Failed to find " + visualizationConfigs.getAaiEntityNodeDescriptors());
+ graphMeta.setAaiEntityNodeDescriptors(null);
+ }
+
+ graphMeta.setNumLinks(linkArrayOutput.size());
+ graphMeta.setNumNodes(flatNodeArray.size());
+ graphMeta.setRenderTimeInMs(preProcessingOpTimeInMs);
+
+ output.setGraphMeta(graphMeta);
+
+ logOptime("generateVisualizationOutput()", opStartTimeInMs);
+
+ return output;
+ }
+
+ /**
+ * Convert visualization output to json.
+ *
+ * @param output the output
+ * @return the string
+ * @throws JsonProcessingException the json processing exception
+ */
+ public String convertVisualizationOutputToJson(D3VisualizationOutput output)
+ throws JsonProcessingException {
+
+ if (output == null) {
+ return null;
+ }
+
+ ObjectWriter ow = new ObjectMapper().writer().withDefaultPrettyPrinter();
+
+ return ow.writeValueAsString(output);
+
+ }
+
+ /**
+ * Builds the links from graph collection.
+ *
+ * @param nodeMap the node map
+ */
+ public void buildLinksFromGraphCollection(Map<String, ActiveInventoryNode> nodeMap) {
+
+ for (ActiveInventoryNode ain : nodeMap.values()) {
+
+ /*
+ * This one is a little bit different, when we iterate over the collection we only want to
+ * draw the links for node that are less than the max traversal depth. We want to only draw
+ * links at a depth of n-1 because we are basing the links on the outbound neighbors from the
+ * current node.
+ */
+
+ if (ain.getNodeDepth() < this.visualizationConfigs.getMaxSelfLinkTraversalDepth()) {
+
+ Collection<String> outboundNeighbors = ain.getOutboundNeighbors();
+
+ for (String outboundNeighbor : outboundNeighbors) {
+
+ SparkyGraphLink nodeLink = new SparkyGraphLink();
+
+ nodeLink.setId(UUID.randomUUID().toString());
+ nodeLink.setSource(ain.getNodeId());
+ nodeLink.setTarget(outboundNeighbor);
+
+ linkArrayOutput.add(nodeLink);
+
+ }
+
+ Collection<String> inboundNeighbors = ain.getInboundNeighbors();
+
+ for (String inboundNeighbor : inboundNeighbors) {
+
+ SparkyGraphLink nodeLink = new SparkyGraphLink();
+
+ nodeLink.setId(UUID.randomUUID().toString());
+ nodeLink.setSource(ain.getNodeId());
+ nodeLink.setTarget(inboundNeighbor);
+
+ linkArrayOutput.add(nodeLink);
+
+ }
+
+
+ } else {
+ if (LOG.isDebugEnabled()) {
+ LOG.debug(AaiUiMsgs.DEBUG_GENERIC, "buildLinks(),"
+ + " Filtering node = " + ain.getNodeId() + " @ depth = "
+ + ain.getNodeDepth());
+ }
+
+ }
+ }
+
+ }
+
+ /**
+ * Builds the flat node array from graph collection.
+ *
+ * @param nodeMap the node map
+ */
+ /*
+ * Recursive function to walk multi-graph nodes and children to build a folded resource target
+ * graph.
+ */
+ public void buildFlatNodeArrayFromGraphCollection(Map<String, ActiveInventoryNode> nodeMap) {
+
+ for (ActiveInventoryNode n : nodeMap.values()) {
+
+ if (n.getNodeDepth() <= this.visualizationConfigs.getMaxSelfLinkTraversalDepth()) {
+
+ SparkyGraphNode jsonNode = new SparkyGraphNode(n, this.visualizationConfigs, this.subConfig);
+
+ jsonNode.getNodeMeta().setClassName(this.visualizationConfigs.getGeneralNodeClassName());
+
+ if (this.visualizationConfigs.isVisualizationDebugEnabled()) {
+
+ NodeDebug nodeDebug = jsonNode.getNodeMeta().getNodeDebug();
+
+ if (nodeDebug != null) {
+ nodeDebug.setProcessingError(n.isProcessingErrorOccurred());
+ nodeDebug.setProcessingErrorCauses(n.getProcessingErrorCauses());
+ }
+ }
+ flatNodeArray.add(jsonNode);
+ } else {
+ if (LOG.isDebugEnabled()) {
+ LOG.debug(AaiUiMsgs.DEBUG_GENERIC,
+ "Filtering node from visualization: " + n.getNodeId() + " @ depth = "
+ + n.getNodeDepth());
+ }
+ }
+ }
+ }
+
+}
Code Review / aai / sparky-be.git / blobdiff