Pregel: Coverty Scan fixes

.gitignore

@@ -105,3 +105,4 @@ npm-debug.log
 
 log-*
 data-*
+cluster-init

Documentation/Books/Manual/Graphs/Pregel/README.mdpp

@@ -15,12 +15,12 @@ This concept enables us to perform distributed graph processing, without the nee
 
 If you are running a single ArangoDB instance in single-server mode, there are no requirements regarding the modeling 
 of your data. All you need is at least one vertex collection and one edge collection. Note that the performance may be
-better if the number of your shards / collections matches the number of CPU cores.
+better, if the number of your shards / collections matches the number of CPU cores.
 
 When you use ArangoDB Community edition in cluster mode, you might need to model your collections in a certain way to
 ensure correct results. For more information see the next section.
 
-## Requirements for Collections (Non Smart Graph)
+## Requirements for Collections in a Cluster (Non Smart Graph)
 
 To enable iterative graph processing for your data, you will need to ensure
 that your vertex and edge collections are sharded in a specific way.
@@ -232,14 +232,15 @@ There are various definitions for centrality, the simplest one being the vertex
 
 ![Illustration of an execution of different centrality measures (Freeman 1977)](centrality_visual.png)
 
-A common definitions of centrality is the \textbf{closeness centrality} (or closeness). 
+
+##### Effective Closeness
+
+A common definitions of centrality is the **closeness centrality** (or closeness). 
 The closeness of a vertex in a graph is the inverse average length of the shortest path between the vertex 
 and all other vertices. For vertices *x*, *y* and shortest distance *d(y,x)* it is defined as
 
 ![Vertex Closeness](closeness.png)
 
-##### Effective Closeness
-
 Effective Closeness approximates the closeness measure. The algorithm works by iteratively estimating the number
 of shortest paths passing through each vertex. The score will approximates the the real closeness score, since
 it is not possible to actually count all shortest paths due to the horrendous O(n^2 * d) memory requirements. 
@@ -255,19 +256,21 @@ algorithm. The algorithm can be used like this
     var handle = pregel.start("effectivecloseness", "yourgraph", resultField: "closeness");
 ```
 
-Another common measure is the *betweenness* centrality: It measures the number of times a vertex is part 
+##### LineRank
-of shortest paths between any two vertices. For a vertex *v* betweenness is defined as
+
+Another common measure is the [betweenness* centrality](https://en.wikipedia.org/wiki/Betweenness_centrality): 
+It measures the number of times a vertex is part  of shortest paths between any pairs of vertices. 
+For a vertex *v* betweenness is defined as
 
 ![Vertex Betweeness](betweeness.png)
 
-Where $\sigma_{xy}$ is the number of shortest paths between $x$ and $y$, and $\sigma_{xy}(v)$ is the 
+Where the σ represents the number of shortest paths between *x* and *y*, and σ(v) represents the 
-number of paths also passing through $v$. The intuitive visualization of these metrics can be seen 
+number of paths also passing through a vertex *v*. By intuition a vertex with higher betweeness centrality will have more information
-below.
+passing through it.
 
 Unfortunately these definitions were not designed with scalability in mind. It is probably impossible to compute them
 efficiently and accurately. Fortunately there are scalable substitutions proposed by **U Kang et.al. 2011**.
 
-##### LineRank
 
 **LineRank** approximates the random walk betweenness of every vertex in a graph. This is the probability that someone starting on
 an arbitary vertex, will visit this node when he randomly chooses edges to visit.

arangod/Pregel/CommonFormats.h

@@ -60,15 +60,14 @@ struct DMIDValue {
 
 struct DMIDMessage {
   DMIDMessage() {}
-  DMIDMessage(PregelID const& pid, float const& val)
+  DMIDMessage(PregelID const& pid, float val) : senderId(pid), weight(val) {}
-      : senderId(pid), weight(val) {}
 
   DMIDMessage(PregelID const& sender, PregelID const& leader)
       : senderId(sender), leaderId(leader) {}
 
   PregelID senderId;
   PregelID leaderId;
-  float weight;
+  float weight = 0;
 };
 
 /// A counter for counting unique vertex IDs using a HyperLogLog sketch.

arangod/Pregel/Conductor.cpp

@@ -89,7 +89,8 @@ Conductor::Conductor(uint64_t executionNumber, TRI_vocbase_t* vocbase,
   if (_lazyLoading) {
     LOG_TOPIC(INFO, Logger::PREGEL) << "Enabled lazy loading";
   }
-  _storeResults = VelocyPackHelper::getBooleanValue(config, "store", true);
+  VPackSlice storeSlice = config.get("store");
+  _storeResults = !storeSlice.isBool() || storeSlice.getBool();
   if (!_storeResults) {
     LOG_TOPIC(INFO, Logger::PREGEL) << "Will keep results in-memory";
   }
@@ -400,13 +401,13 @@ void Conductor::startRecovery() {
   TRI_ASSERT(ioService != nullptr);
 
   // let's wait for a final state in the cluster
-  _boost_timer.reset(new boost::asio::deadline_timer(*ioService,
+  _boost_timer.reset(new boost::asio::deadline_timer(
-                                                     boost::posix_time::seconds(2)));
+      *ioService, boost::posix_time::seconds(2)));
   _boost_timer->async_wait([this](const boost::system::error_code& error) {
     _boost_timer.reset();
 
-    if (error == boost::asio::error::operation_aborted
+    if (error == boost::asio::error::operation_aborted ||
-        || _state != ExecutionState::RECOVERING) {
+        _state != ExecutionState::RECOVERING) {
       return;  // seems like we are canceled
     }
     std::vector<ServerID> goodServers;

arangod/Pregel/Conductor.h

@@ -25,13 +25,13 @@
 
 #include <string>
 
+#include <boost/date_time/posix_time/posix_time.hpp>
 #include "Basics/Common.h"
 #include "Basics/Mutex.h"
 #include "Cluster/ClusterComm.h"
 #include "Cluster/ClusterInfo.h"
 #include "Pregel/Statistics.h"
 #include "VocBase/vocbase.h"
-#include <boost/date_time/posix_time/posix_time.hpp>
 
 namespace arangodb {
 namespace pregel {
@@ -87,7 +87,9 @@ class Conductor {
   uint64_t _totalVerticesCount = 0;
   uint64_t _totalEdgesCount = 0;
   /// some tracking info
-  double _startTimeSecs = 0, _computationStartTimeSecs, _endTimeSecs = 0;
+  double _startTimeSecs = 0;
+  double _computationStartTimeSecs = 0;
+  double _endTimeSecs = 0;
   std::unique_ptr<boost::asio::deadline_timer> _boost_timer;
 
   bool _startGlobalStep();

arangod/Pregel/Graph.h

@@ -33,13 +33,13 @@ namespace pregel {
 typedef std::string PregelKey;
 // typedef uint64_t PregelKey;
 typedef uint16_t PregelShard;
-const PregelShard invalid_prgl_shard = -1;
+const PregelShard InvalidPregelShard = -1;
 
 struct PregelID {
   PregelShard shard;
   PregelKey key;
 
-  PregelID() : shard(invalid_prgl_shard), key("") {}
+  PregelID() : shard(InvalidPregelShard), key("") {}
   PregelID(PregelShard s, PregelKey const& k) : shard(s), key(k) {}
   // PregelID(PregelShard s, std::string const& k) : shard(s),
   // key(std::stoull(k)) {}
@@ -53,7 +53,7 @@ struct PregelID {
   }
 
   bool inline isValid() const {
-    return shard != invalid_prgl_shard && !key.empty();
+    return shard != InvalidPregelShard && !key.empty();
   }
 };
 
@@ -73,7 +73,7 @@ class Edge {
 
  public:
   // EdgeEntry() : _nextEntryOffset(0), _dataSize(0), _vertexIDSize(0) {}
-  Edge() {}
+  Edge() : _targetShard(InvalidPregelShard) {}
   Edge(PregelShard target, PregelKey const& key)
       : _targetShard(target), _toKey(key) {}
 
@@ -99,14 +99,9 @@ class VertexEntry {
   bool _active = true;
 
  public:
-  VertexEntry() {}
+  VertexEntry() : _shard(InvalidPregelShard) {}
   VertexEntry(PregelShard shard, PregelKey const& key)
-      : _shard(shard),
+      : _shard(shard), _key(key) {}
-        _key(key),
-        _vertexDataOffset(0),
-        _edgeDataOffset(0),
-        _edgeCount(0),
-        _active(true) {}  //_vertexIDSize(0)
 
   inline size_t getVertexDataOffset() const { return _vertexDataOffset; }
   inline size_t getEdgeDataOffset() const { return _edgeDataOffset; }

arangod/Pregel/GraphStore.h

@@ -56,7 +56,7 @@ template <typename V, typename E>
 class GraphStore {
   VocbaseGuard _vocbaseGuard;
   const std::unique_ptr<GraphFormat<V, E>> _graphFormat;
-  WorkerConfig* _config;
+  WorkerConfig* _config = nullptr;
 
   std::vector<VertexEntry> _index;
   TypedBuffer<V>* _vertexData = nullptr;

arangod/Pregel/MasterContext.h

@@ -39,7 +39,7 @@ class MasterContext {
   uint64_t _edgeCount = 0;
   // Should cause the master to tell everyone to enter the next phase
   bool _enterNextGSS = false;
-  AggregatorHandler* _aggregators;
+  AggregatorHandler* _aggregators = nullptr;
 
  public:
   MasterContext(){};

arangod/Pregel/OutgoingCache.h

@@ -55,7 +55,7 @@ class OutCache {
  protected:
   WorkerConfig const* _config;
   MessageFormat<M> const* _format;
-  InCache<M>* _localCache;
+  InCache<M>* _localCache = nullptr;
   InCache<M>* _localCacheNextGSS = nullptr;
   std::string _baseUrl;
   uint32_t _batchSize = 1000;

arangod/Pregel/TypedBuffer.h

@@ -41,7 +41,7 @@ template <typename T>
 struct TypedBuffer {
   /// close file (see close() )
   virtual ~TypedBuffer(){};
-  TypedBuffer() {}
+  TypedBuffer() : _ptr(nullptr) {}
 
   /// @brief return whether the datafile is a physical file (true) or an
   /// anonymous mapped region (false)

arangod/Pregel/VertexComputation.h

@@ -45,11 +45,11 @@ class VertexContext {
 
   uint64_t _gss = 0;
   uint64_t _lss = 0;
-  WorkerContext* _context;
+  WorkerContext* _context = nullptr;
-  GraphStore<V, E>* _graphStore;
+  GraphStore<V, E>* _graphStore = nullptr;
-  AggregatorHandler* _readAggregators;
+  AggregatorHandler* _readAggregators = nullptr;
-  AggregatorHandler* _writeAggregators;
+  AggregatorHandler* _writeAggregators = nullptr;
-  VertexEntry* _vertexEntry;
+  VertexEntry* _vertexEntry = nullptr;
 
  public:
   virtual ~VertexContext() {}
@@ -101,7 +101,7 @@ class VertexContext {
 template <typename V, typename E, typename M>
 class VertexComputation : public VertexContext<V, E, M> {
   friend class Worker<V, E, M>;
-  OutCache<M>* _cache;
+  OutCache<M>* _cache = nullptr;
   bool _enterNextGSS = false;
 
  public:

arangod/Pregel/Worker.cpp

@@ -59,18 +59,19 @@ using namespace arangodb::pregel;
 template <typename V, typename E, typename M>
 Worker<V, E, M>::Worker(TRI_vocbase_t* vocbase, Algorithm<V, E, M>* algo,
                         VPackSlice initConfig)
-    : _config(vocbase, initConfig), _algorithm(algo) {
+    : _state(WorkerState::IDLE),
+      _config(vocbase, initConfig),
+      _algorithm(algo),
+      _nextGSSSendMessageCount(0) {
   MUTEX_LOCKER(guard, _commandMutex);
 
   VPackSlice userParams = initConfig.get(Utils::userParametersKey);
-  _state = WorkerState::IDLE;
   _workerContext.reset(algo->workerContext(userParams));
   _messageFormat.reset(algo->messageFormat());
   _messageCombiner.reset(algo->messageCombiner());
   _conductorAggregators.reset(new AggregatorHandler(algo));
   _workerAggregators.reset(new AggregatorHandler(algo));
   _graphStore.reset(new GraphStore<V, E>(vocbase, _algorithm->inputFormat()));
-  _nextGSSSendMessageCount = 0;
   if (_config.asynchronousMode()) {
     _messageBatchSize = _algorithm->messageBatchSize(_config, _messageStats);
   } else {
@@ -112,9 +113,6 @@ Worker<V, E, M>::Worker(TRI_vocbase_t* vocbase, Algorithm<V, E, M>* algo,
   }
 }
 
-/*template <typename M>
-GSSContext::~GSSContext() {}*/
-
 template <typename V, typename E, typename M>
 Worker<V, E, M>::~Worker() {
   LOG_TOPIC(DEBUG, Logger::PREGEL) << "Called ~Worker()";
@@ -574,10 +572,11 @@ void Worker<V, E, M>::_continueAsync() {
   TRI_ASSERT(ioService != nullptr);
 
   // wait for new messages before beginning to process
-  int64_t milli = _writeCache->containedMessageCount() < _messageBatchSize ? 50 : 5;
+  int64_t milli =
+      _writeCache->containedMessageCount() < _messageBatchSize ? 50 : 5;
   // start next iteration in $milli mseconds.
-  _boost_timer.reset(new boost::asio::deadline_timer(*ioService,
+  _boost_timer.reset(new boost::asio::deadline_timer(
-                                                     boost::posix_time::millisec(milli)));
+      *ioService, boost::posix_time::millisec(milli)));
   _boost_timer->async_wait([this](const boost::system::error_code& error) {
     if (error != boost::asio::error::operation_aborted) {
       {  // swap these pointers atomically

arangod/Pregel/Worker.h

@@ -24,6 +24,7 @@
 #define ARANGODB_PREGEL_WORKER_H 1
 
 #include <atomic>
+#include <boost/date_time/posix_time/posix_time.hpp>
 #include "Basics/Common.h"
 #include "Basics/Mutex.h"
 #include "Basics/ReadWriteLock.h"
@@ -32,7 +33,6 @@
 #include "Pregel/Statistics.h"
 #include "Pregel/WorkerConfig.h"
 #include "Pregel/WorkerContext.h"
-#include <boost/date_time/posix_time/posix_time.hpp>
 
 struct TRI_vocbase_t;
 namespace arangodb {
@@ -100,7 +100,7 @@ class Worker : public IWorker {
 
   // only valid while recovering to determine the offset
   // where new vertices were inserted
-  size_t _preRecoveryTotal;
+  size_t _preRecoveryTotal = 0;
 
   std::unique_ptr<AggregatorHandler> _conductorAggregators;
   std::unique_ptr<AggregatorHandler> _workerAggregators;

arangod/Pregel/WorkerContext.h

@@ -58,7 +58,11 @@ class WorkerContext {
   virtual void postApplication(){};
 
  public:
-  WorkerContext() {}
+  WorkerContext()
+      : _vertexCount(0),
+        _edgeCount(0),
+        _readAggregators(nullptr),
+        _writeAggregators(nullptr) {}
   virtual ~WorkerContext() {}
 
   inline uint64_t vertexCount() const { return _vertexCount; }

js/server/tests/shell/shell-pregel.js

@@ -44,11 +44,9 @@ function testAlgo(a, p) {
   var key = db._pregelStart(a, vColl, eColl, p);
   var i = 1000;
   do {
-    console.log("Waiting...");
     internal.wait(1);
     var doc = db._pregelStatus(key);
     if (doc.state !== "running") {
-      console.log("Finished algorithm " + a);
 
       db[vColl].all().toArray()
       .forEach(function(d) {
@@ -60,7 +58,6 @@ function testAlgo(a, p) {
                    }
                  }
                });
-      console.log("Done executing " + a + " : " + key);
       break;
     }
   } while(i-- >= 0);