Wednesday, June 07, 2017

Azure IoT Edge

By using containers, Azure IoT Edge enables migration of functionality between "cloud" and "cloud edge". Original promise of Java, realized in a bit more generic way. 

Azure IoT Edge | Microsoft Azure

"IoT Edge provides easy orchestration between code and services, so they flow securely between cloud and edge to distribute intelligence across IoT devices."

"Extend cloud intelligence to edge devices
  • Run artificial intelligence at the edge
  • Perform edge analytics
  • Deploy IoT solutions from cloud to edge
  • Manage devices centrally from the cloud
  • Operate with offline and intermittent connectivity
  • Enable real-time decisions
  • Connect new and legacy devices
  • Reduce bandwidth costs"
Azure IoT Edge | Build 2017 | Channel 9

Azure Cosmos DB Graph APIs

Introduction to Azure Cosmos DB Graph APIs | Microsoft Docs
Azure Cosmos DB graph architecture
Graph language "Gremlin"

TinkerPop3 Documentation


"A graph’s structure is the topology formed by the explicit references between its vertices, edges, and properties. A vertex has incident edges. A vertex is adjacent to another vertex if they share an incident edge. A property is attached to an element and an element has a set of properties. A property is a key/value pair, where the key is always a character String. The graph structure API of TinkerPop3 provides the methods necessary to create such a structure. The TinkerPop graph previously diagrammed can be created with the following Java 8 code. Note that this graph is available as an in-memory TinkerGraph using TinkerFactory.createClassic()."














Graph graph = TinkerGraph.open(); (1) Vertex marko = graph.addVertex(T.label, "person", T.id, 1, "name", "marko", "age", 29); (2) Vertex vadas = graph.addVertex(T.label, "person", T.id, 2, "name", "vadas", "age", 27); Vertex lop = graph.addVertex(T.label, "software", T.id, 3, "name", "lop", "lang", "java"); Vertex josh = graph.addVertex(T.label, "person", T.id, 4, "name", "josh", "age", 32); Vertex ripple = graph.addVertex(T.label, "software", T.id, 5, "name", "ripple", "lang", "java"); Vertex peter = graph.addVertex(T.label, "person", T.id, 6, "name", "peter", "age", 35); marko.addEdge("knows", vadas, T.id, 7, "weight", 0.5f); (3) marko.addEdge("knows", josh, T.id, 8, "weight", 1.0f); marko.addEdge("created", lop, T.id, 9, "weight", 0.4f); josh.addEdge("created", ripple, T.id, 10, "weight", 1.0f); josh.addEdge("created", lop, T.id, 11, "weight", 0.4f); peter.addEdge("created", lop, T.id, 12, "weight", 0.2f);


Alternative, a bit simpler to use, graph query language is Cypher from Neo4j.
graph databases - Neo4j - Cypher vs Gremlin query language - Stack Overflow



jbmusso/gremlin-javascript: JavaScript graph database client for TinkerPop3 Gremlin Server @GitHub
client.execute('g.V().has("name", name)', { name: 'Alice' }, (err, results) => {
  if (err) return console.error(err);
  console.log(results);
})

The Gremlin Graph Traversal Language @ SlideShare

Azure Cosmos DB: NoSQL capabilities everyone should know about | Build 2017 | Channel 9



How to build globally-distributed, fast, billion-user applications with Azure Cosmos DB | Build 2017 | Channel 9