diff --git a/docs/graphx-programming-guide.md b/docs/graphx-programming-guide.md index 9dea9b5904d2da0be5d643cfad4067202966fac0..81cf17475fb6007660937bc49e66ef7e50cd05df 100644 --- a/docs/graphx-programming-guide.md +++ b/docs/graphx-programming-guide.md @@ -132,7 +132,7 @@ var graph: Graph[VertexProperty, String] = null Like RDDs, property graphs are immutable, distributed, and fault-tolerant. Changes to the values or structure of the graph are accomplished by producing a new graph with the desired changes. Note -that substantial parts of the original graph (i.e., unaffected structure, attributes, and indicies) +that substantial parts of the original graph (i.e., unaffected structure, attributes, and indices) are reused in the new graph reducing the cost of this inherently functional data structure. The graph is partitioned across the executors using a range of vertex partitioning heuristics. As with RDDs, each partition of the graph can be recreated on a different machine in the event of a failure. diff --git a/docs/hardware-provisioning.md b/docs/hardware-provisioning.md index 60ecb4f483afabfcaeffd4e96a3e64849f49d0b2..bb6f616b18a241704fa77fa75bbe10c00580718b 100644 --- a/docs/hardware-provisioning.md +++ b/docs/hardware-provisioning.md @@ -22,7 +22,7 @@ Hadoop and Spark on a common cluster manager like [Mesos](running-on-mesos.html) * If this is not possible, run Spark on different nodes in the same local-area network as HDFS. -* For low-latency data stores like HBase, it may be preferrable to run computing jobs on different +* For low-latency data stores like HBase, it may be preferable to run computing jobs on different nodes than the storage system to avoid interference. # Local Disks diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md index 78ae6a7407467296a8a71a7252407205817fa342..0a6a0397d9570f9d4ed4daecd25e0d624425d6d1 100644 --- a/docs/streaming-programming-guide.md +++ b/docs/streaming-programming-guide.md @@ -1259,7 +1259,7 @@ dstream.foreachRDD(sendRecord) </div> This is incorrect as this requires the connection object to be serialized and sent from the -driver to the worker. Such connection objects are rarely transferrable across machines. This +driver to the worker. Such connection objects are rarely transferable across machines. This error may manifest as serialization errors (connection object not serializable), initialization errors (connection object needs to be initialized at the workers), etc. The correct solution is to create the connection object at the worker.