Rewrote roxygen and added local sequential context

R/azureDSVM-package.R

@@ -1,6 +1,6 @@
 #' AzureDSVM
 #'
-#' Support data science analytics with Azure resources.
+#' Support data science analytics with Azure Data Science Virtual Machine.
 #'
 #' @name AzureDSVM-package
 #' @aliases AzureDSVM

R/computeInterface.R

@@ -1,9 +1,15 @@
 #' @title Create an compute interface object that handles interaction with remote instance.
+#' 
 #' @param remote URL of remote instance.
+#' 
 #' @param user User name.
+#' 
 #' @param script R script with full path for execution at remote instance.
+#' 
 #' @param config Configuration for remote execution. Settings include computing context, data reference, etc.
+#' 
 #' @return An S3 compute interface object.
+#' 
 #' @export
 createComputeInterface <- function(remote,
                                    user,
@@ -41,14 +47,25 @@ createComputeInterface <- function(remote,
 }
 
 #' @title Set configuration for the compute interface object.
+#' 
 #' @param object An S3 compute interface object.
+#' 
 #' @param machine_list List of remote instances that execute R scripts.
+#' 
 #' @param dns_list DNS of the remote instances.
+#' 
 #' @param machine_user User name of the remote instances.
+#' 
 #' @param master Master node of the machine.
+#' 
 #' @param slaves Slave nodes of the machine.
+#' 
 #' @param data Reference to data used in the analytics.
+#' 
 #' @param context Computing context available in Microsoft R Server for running the analytics.
+#' 
+#' @return The compute interface object in which the informate needed for remote executioni is contained.
+#' 
 #' @export
 setConfig <- function(object,
                       machine_list,
@@ -72,8 +89,11 @@ setConfig <- function(object,
 }
 
 #' @title Dump the interface configuration.
+#' 
 #' @param object The compute interface object.
+#' 
 #' @return No return. Print compute interface object information.
+#' 
 #' @export
 dumpInterface <- function(object) {
   cat(
@@ -101,7 +121,11 @@ dumpInterface <- function(object) {
 }
 
 #' @title Update a worker script with compute interface object configuration.
+#' 
 #' @param object compute interface object.
+#' 
+#' @details The update script basically updates the computing context specific information into the worker script that is going to be executed on a remote instance. It saves the work of data scientists to rewrite initial set-ups for different computing contexts.
+#' 
 #' @export
 updateScript <- function(object) {
   if (!file.exists(object$script) || length(object$script) == 0)
@@ -219,6 +243,24 @@ updateScript <- function(object) {
       "# ---------------------------------------------------------------------------\n",
       sep="\n"
     )
+  } else if (object$config$CI_CONTEXT == "localSequential") {
+    codes_head <- paste(
+      codes_head,
+      paste("CI_MACHINES <-", "c(", paste(shQuote(unlist(object$config$CI_MACHINES)), collapse=", "), ")"),
+      paste("CI_DNS <-", "c(", paste(shQuote(unlist(object$config$CI_DNS)), collapse=", "), ")"),
+      paste("CI_VMUSER <-", "c(", paste(shQuote(unlist(object$config$CI_VMUSER)), collapse=", "), ")"),
+      paste("CI_MASTER <-", "c(", paste(shQuote(unlist(object$config$CI_MASTER)), collapse=", "), ")"),
+      paste("CI_SLAVES <-", "c(", paste(shQuote(unlist(object$config$CI_SLAVES)), collapse=", "), ")"),
+      paste("CI_DATA <-", paste(shQuote(unlist(object$config$CI_DATA)), collapse=", ")),
+      paste("CI_CONTEXT <-", paste(shQuote(unlist(object$config$CI_CONTEXT)), collapse=", ")),
+      "\nlibrary(RevoScaleR)",
+      "# --------- Set compute context",
+      "rxSetComputeContext(RxLocalSeq())",
+      "# ---------------------------------------------------------------------------",
+      "# END OF THE HEADER ADDED BY COMPUTE INTERFACE",
+      "# ---------------------------------------------------------------------------\n",
+      sep="\n"
+    )
   } else {
     stop(paste("Specify a context from \"localParallel\", \"clusterParallel\",",
                "\"Hadoop\", \"Spark\", or \"Teradata\"."))

R/deployDSVM.R

@@ -51,7 +51,7 @@ deployDSVM <- function(context,
                        location,
                        hostname,
                        username,
-                       size="Standard_DS2_v2",
+                       size="Standard_D1_v2",
                        os="Linux",
                        authen=ifelse(os=="Linux", "Key", "Password"),
                        pubkey="",

R/expenseCalculator.R

@@ -1,7 +1,7 @@
 #' @title Get data consumption of an Azure subscription for a time period. Aggregation method can be either daily based or hourly based.
-#' @note Formats of start time point and end time point follow ISO 8601 standard. Say if one would like to calculate data consumption between Feb 21, 2017 to Feb 25, 2017, the inputs should be "2017-02-21 00:00:00" and "2017-02-25 00:00:00", for start time point and end time point, respectively. For hourly based calculation, note there should be no minute and second included.
+#' @note Formats of start time point and end time point follow ISO 8601 standard. Say if one would like to calculate data consumption between Feb 21, 2017 to Feb 25, 2017, the inputs should be "2017-02-21 00:00:00" and "2017-02-25 00:00:00", for start time point and end time point, respectively. Note if the aggregation granularity is hourly based, and the time difference between starting and ending point is less than an hour, data consumption will be that in the past one hour.
 #' @param context AzureSMR context object.
-#' @param instance Instance of Azure instance name that one would like to check expense. For example, it can be the name of a virtual machine.
+#' @param instance Instance of Azure DSVM name that one would like to check expense. 
 #' @param timeStart Start time.
 #' @param timeEnd End time.
 #' @param granularity Aggregation granularity. Can be either "Daily" or "Hourly".