R/sparkR.R

Defines functions doServerAuth sparkCheckInstall processSparkPackages processSparkJars getClientModeSparkSubmitOpts getLocalProperty setLocalProperty setJobDescription cancelJobGroup clearJobGroup setJobGroup sparkR.uiWebUrl sparkR.session sparkRHive.init sparkRSQL.init sparkR.sparkContext sparkR.init sparkR.stop sparkR.session.stop connExists

Documented in cancelJobGroup clearJobGroup getLocalProperty setJobDescription setJobGroup setLocalProperty sparkRHive.init sparkR.init sparkR.session sparkR.session.stop sparkRSQL.init sparkR.stop sparkR.uiWebUrl

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You 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.
#

.sparkREnv <- new.env()

# Utility function that returns TRUE if we have an active connection to the
# backend and FALSE otherwise
connExists <- function(env) {
  tryCatch({
    exists(".sparkRCon", envir = env) && isOpen(env[[".sparkRCon"]])
  },
  error = function(err) {
    return(FALSE)
  })
}

#' Stop the Spark Session and Spark Context
#'
#' Stop the Spark Session and Spark Context.
#'
#' Also terminates the backend this R session is connected to.
#' @rdname sparkR.session.stop
#' @name sparkR.session.stop
#' @note sparkR.session.stop since 2.0.0
sparkR.session.stop <- function() {
  env <- .sparkREnv
  if (exists(".sparkRCon", envir = env)) {
    if (exists(".sparkRjsc", envir = env)) {
      sc <- get(".sparkRjsc", envir = env)
      callJMethod(sc, "stop")
      rm(".sparkRjsc", envir = env)

      if (exists(".sparkRsession", envir = env)) {
        rm(".sparkRsession", envir = env)
      }
    }

    # Remove the R package lib path from .libPaths()
    if (exists(".libPath", envir = env)) {
      libPath <- get(".libPath", envir = env)
      .libPaths(.libPaths()[.libPaths() != libPath])
    }

    if (exists(".backendLaunched", envir = env)) {
      callJStatic("SparkRHandler", "stopBackend")
    }

    # Also close the connection and remove it from our env
    conn <- get(".sparkRCon", envir = env)
    close(conn)

    rm(".sparkRCon", envir = env)
    rm(".scStartTime", envir = env)
  }

  if (exists(".monitorConn", envir = env)) {
    conn <- get(".monitorConn", envir = env)
    close(conn)
    rm(".monitorConn", envir = env)
  }

  # Clear all broadcast variables we have
  # as the jobj will not be valid if we restart the JVM
  clearBroadcastVariables()

  # Clear jobj maps
  clearJobjs()
}

#' @rdname sparkR.session.stop
#' @name sparkR.stop
#' @note sparkR.stop since 1.4.0
sparkR.stop <- function() {
  sparkR.session.stop()
}

#' (Deprecated) Initialize a new Spark Context
#'
#' This function initializes a new SparkContext.
#'
#' @param master The Spark master URL
#' @param appName Application name to register with cluster manager
#' @param sparkHome Spark Home directory
#' @param sparkEnvir Named list of environment variables to set on worker nodes
#' @param sparkExecutorEnv Named list of environment variables to be used when launching executors
#' @param sparkJars Character vector of jar files to pass to the worker nodes
#' @param sparkPackages Character vector of package coordinates
#' @seealso \link{sparkR.session}
#' @rdname sparkR.init-deprecated
#' @examples
#'\dontrun{
#' sc <- sparkR.init("local[2]", "SparkR", "/home/spark")
#' sc <- sparkR.init("local[2]", "SparkR", "/home/spark",
#'                  list(spark.executor.memory="1g"))
#' sc <- sparkR.init("yarn-client", "SparkR", "/home/spark",
#'                  list(spark.executor.memory="4g"),
#'                  list(LD_LIBRARY_PATH="/directory of JVM libraries (libjvm.so) on workers/"),
#'                  c("one.jar", "two.jar", "three.jar"),
#'                  c("com.databricks:spark-avro_2.11:2.0.1"))
#'}
#' @note sparkR.init since 1.4.0
sparkR.init <- function(
  master = "",
  appName = "SparkR",
  sparkHome = Sys.getenv("SPARK_HOME"),
  sparkEnvir = list(),
  sparkExecutorEnv = list(),
  sparkJars = "",
  sparkPackages = "") {
  .Deprecated("sparkR.session")
  sparkR.sparkContext(master,
     appName,
     sparkHome,
     convertNamedListToEnv(sparkEnvir),
     convertNamedListToEnv(sparkExecutorEnv),
     sparkJars,
     sparkPackages)
}

# Internal function to handle creating the SparkContext.
sparkR.sparkContext <- function(
  master = "",
  appName = "SparkR",
  sparkHome = Sys.getenv("SPARK_HOME"),
  sparkEnvirMap = new.env(),
  sparkExecutorEnvMap = new.env(),
  sparkJars = "",
  sparkPackages = "") {

  if (exists(".sparkRjsc", envir = .sparkREnv)) {
    cat(paste("Re-using existing Spark Context.",
              "Call sparkR.session.stop() or restart R to create a new Spark Context\n"))
    return(get(".sparkRjsc", envir = .sparkREnv))
  }

  jars <- processSparkJars(sparkJars)
  packages <- processSparkPackages(sparkPackages)

  existingPort <- Sys.getenv("EXISTING_SPARKR_BACKEND_PORT", "")
  connectionTimeout <- as.numeric(Sys.getenv("SPARKR_BACKEND_CONNECTION_TIMEOUT", "6000"))
  if (existingPort != "") {
    if (length(packages) != 0) {
      warning("sparkPackages has no effect when using spark-submit or sparkR shell, ",
              "please use the --packages commandline instead")
    }
    backendPort <- existingPort
    authSecret <- Sys.getenv("SPARKR_BACKEND_AUTH_SECRET")
    if (nchar(authSecret) == 0) {
      stop("Auth secret not provided in environment.")
    }
  } else {
    path <- tempfile(pattern = "backend_port")
    submitOps <- getClientModeSparkSubmitOpts(
        Sys.getenv("SPARKR_SUBMIT_ARGS", "sparkr-shell"),
        sparkEnvirMap)
    invisible(checkJavaVersion())
    launchBackend(
        args = path,
        sparkHome = sparkHome,
        jars = jars,
        sparkSubmitOpts = submitOps,
        packages = packages)
    # wait atmost 100 seconds for JVM to launch
    wait <- 0.1
    for (i in 1:25) {
      Sys.sleep(wait)
      if (file.exists(path)) {
        break
      }
      wait <- wait * 1.25
    }
    if (!file.exists(path)) {
      stop("JVM is not ready after 10 seconds")
    }
    f <- file(path, open = "rb")
    backendPort <- readInt(f)
    monitorPort <- readInt(f)
    rLibPath <- readString(f)
    connectionTimeout <- readInt(f)

    # Don't use readString() so that we can provide a useful
    # error message if the R and Java versions are mismatched.
    authSecretLen <- readInt(f)
    if (length(authSecretLen) == 0 || authSecretLen == 0) {
      stop("Unexpected EOF in JVM connection data. Mismatched versions?")
    }
    authSecret <- readStringData(f, authSecretLen)
    close(f)
    file.remove(path)
    if (length(backendPort) == 0 || backendPort == 0 ||
        length(monitorPort) == 0 || monitorPort == 0 ||
        length(rLibPath) != 1 || length(authSecret) == 0) {
      stop("JVM failed to launch")
    }

    monitorConn <- socketConnection(port = monitorPort, blocking = TRUE,
                                    timeout = connectionTimeout, open = "wb")
    doServerAuth(monitorConn, authSecret)

    assign(".monitorConn", monitorConn, envir = .sparkREnv)
    assign(".backendLaunched", 1, envir = .sparkREnv)
    if (rLibPath != "") {
      assign(".libPath", rLibPath, envir = .sparkREnv)
      .libPaths(c(rLibPath, .libPaths()))
    }
  }

  .sparkREnv$backendPort <- backendPort
  tryCatch({
    connectBackend("localhost", backendPort, timeout = connectionTimeout, authSecret = authSecret)
  },
  error = function(err) {
    stop("Failed to connect JVM\n")
  })

  if (nchar(sparkHome) != 0) {
    sparkHome <- suppressWarnings(normalizePath(sparkHome))
  }

  if (is.null(sparkExecutorEnvMap$LD_LIBRARY_PATH)) {
    sparkExecutorEnvMap[["LD_LIBRARY_PATH"]] <-
      paste0("$LD_LIBRARY_PATH:", Sys.getenv("LD_LIBRARY_PATH"))
  }

  # Classpath separator is ";" on Windows
  # URI needs four /// as from http://stackoverflow.com/a/18522792
  if (.Platform$OS.type == "unix") {
    uriSep <- "//"
  } else {
    uriSep <- "////"
  }
  localJarPaths <- lapply(jars,
                          function(j) { utils::URLencode(paste0("file:", uriSep, j)) })

  # Set the start time to identify jobjs
  # Seconds resolution is good enough for this purpose, so use ints
  assign(".scStartTime", as.integer(Sys.time()), envir = .sparkREnv)

  assign(
    ".sparkRjsc",
    callJStatic(
      "org.apache.spark.api.r.RRDD",
      "createSparkContext",
      master,
      appName,
      as.character(sparkHome),
      localJarPaths,
      sparkEnvirMap,
      sparkExecutorEnvMap),
    envir = .sparkREnv
  )

  sc <- get(".sparkRjsc", envir = .sparkREnv)

  # Register a finalizer to sleep 1 seconds on R exit to make RStudio happy
  reg.finalizer(.sparkREnv, function(x) { Sys.sleep(1) }, onexit = TRUE)

  sc
}

#' (Deprecated) Initialize a new SQLContext
#'
#' This function creates a SparkContext from an existing JavaSparkContext and
#' then uses it to initialize a new SQLContext
#'
#' Starting SparkR 2.0, a SparkSession is initialized and returned instead.
#' This API is deprecated and kept for backward compatibility only.
#'
#' @param jsc The existing JavaSparkContext created with SparkR.init()
#' @seealso \link{sparkR.session}
#' @rdname sparkRSQL.init-deprecated
#' @examples
#'\dontrun{
#' sc <- sparkR.init()
#' sqlContext <- sparkRSQL.init(sc)
#'}
#' @note sparkRSQL.init since 1.4.0
sparkRSQL.init <- function(jsc = NULL) {
  .Deprecated("sparkR.session")

  if (exists(".sparkRsession", envir = .sparkREnv)) {
    return(get(".sparkRsession", envir = .sparkREnv))
  }

  # Default to without Hive support for backward compatibility.
  sparkR.session(enableHiveSupport = FALSE)
}

#' (Deprecated) Initialize a new HiveContext
#'
#' This function creates a HiveContext from an existing JavaSparkContext
#'
#' Starting SparkR 2.0, a SparkSession is initialized and returned instead.
#' This API is deprecated and kept for backward compatibility only.
#'
#' @param jsc The existing JavaSparkContext created with SparkR.init()
#' @seealso \link{sparkR.session}
#' @rdname sparkRHive.init-deprecated
#' @examples
#'\dontrun{
#' sc <- sparkR.init()
#' sqlContext <- sparkRHive.init(sc)
#'}
#' @note sparkRHive.init since 1.4.0
sparkRHive.init <- function(jsc = NULL) {
  .Deprecated("sparkR.session")

  if (exists(".sparkRsession", envir = .sparkREnv)) {
    return(get(".sparkRsession", envir = .sparkREnv))
  }

  # Default to without Hive support for backward compatibility.
  sparkR.session(enableHiveSupport = TRUE)
}

#' Get the existing SparkSession or initialize a new SparkSession.
#'
#' SparkSession is the entry point into SparkR. \code{sparkR.session} gets the existing
#' SparkSession or initializes a new SparkSession.
#' Additional Spark properties can be set in \code{...}, and these named parameters take priority
#' over values in \code{master}, \code{appName}, named lists of \code{sparkConfig}.
#'
#' When called in an interactive session, this method checks for the Spark installation, and, if not
#' found, it will be downloaded and cached automatically. Alternatively, \code{install.spark} can
#' be called manually.
#'
#' A default warehouse is created automatically in the current directory when a managed table is
#' created via \code{sql} statement \code{CREATE TABLE}, for example. To change the location of the
#' warehouse, set the named parameter \code{spark.sql.warehouse.dir} to the SparkSession. Along with
#' the warehouse, an accompanied metastore may also be automatically created in the current
#' directory when a new SparkSession is initialized with \code{enableHiveSupport} set to
#' \code{TRUE}, which is the default. For more details, refer to Hive configuration at
#' \url{http://spark.apache.org/docs/latest/sql-programming-guide.html#hive-tables}.
#'
#' For details on how to initialize and use SparkR, refer to SparkR programming guide at
#' \url{http://spark.apache.org/docs/latest/sparkr.html#starting-up-sparksession}.
#'
#' @param master the Spark master URL.
#' @param appName application name to register with cluster manager.
#' @param sparkHome Spark Home directory.
#' @param sparkConfig named list of Spark configuration to set on worker nodes.
#' @param sparkJars character vector of jar files to pass to the worker nodes.
#' @param sparkPackages character vector of package coordinates
#' @param enableHiveSupport enable support for Hive, fallback if not built with Hive support; once
#'        set, this cannot be turned off on an existing session
#' @param ... named Spark properties passed to the method.
#' @examples
#'\dontrun{
#' sparkR.session()
#' df <- read.json(path)
#'
#' sparkR.session("local[2]", "SparkR", "/home/spark")
#' sparkR.session("yarn", "SparkR", "/home/spark",
#'                list(spark.executor.memory="4g", spark.submit.deployMode="client"),
#'                c("one.jar", "two.jar", "three.jar"),
#'                c("com.databricks:spark-avro_2.12:2.0.1"))
#' sparkR.session(spark.master = "yarn", spark.submit.deployMode = "client",
#                 spark.executor.memory = "4g")
#'}
#' @note sparkR.session since 2.0.0
sparkR.session <- function(
  master = "",
  appName = "SparkR",
  sparkHome = Sys.getenv("SPARK_HOME"),
  sparkConfig = list(),
  sparkJars = "",
  sparkPackages = "",
  enableHiveSupport = TRUE,
  ...) {

  sparkConfigMap <- convertNamedListToEnv(sparkConfig)
  namedParams <- list(...)
  if (length(namedParams) > 0) {
    paramMap <- convertNamedListToEnv(namedParams)
    # Override for certain named parameters
    if (exists("spark.master", envir = paramMap)) {
      master <- paramMap[["spark.master"]]
    }
    if (exists("spark.app.name", envir = paramMap)) {
      appName <- paramMap[["spark.app.name"]]
    }
    overrideEnvs(sparkConfigMap, paramMap)
  }

  deployMode <- ""
  if (exists("spark.submit.deployMode", envir = sparkConfigMap)) {
    deployMode <- sparkConfigMap[["spark.submit.deployMode"]]
  }

  if (!exists("spark.r.sql.derby.temp.dir", envir = sparkConfigMap)) {
    sparkConfigMap[["spark.r.sql.derby.temp.dir"]] <- tempdir()
  }

  if (!exists(".sparkRjsc", envir = .sparkREnv)) {
    retHome <- sparkCheckInstall(sparkHome, master, deployMode)
    if (!is.null(retHome)) sparkHome <- retHome
    sparkExecutorEnvMap <- new.env()
    sparkR.sparkContext(master, appName, sparkHome, sparkConfigMap, sparkExecutorEnvMap,
       sparkJars, sparkPackages)
    stopifnot(exists(".sparkRjsc", envir = .sparkREnv))
  }

  if (exists(".sparkRsession", envir = .sparkREnv)) {
    sparkSession <- get(".sparkRsession", envir = .sparkREnv)
    # Apply config to Spark Context and Spark Session if already there
    # Cannot change enableHiveSupport
    callJStatic("org.apache.spark.sql.api.r.SQLUtils",
                "setSparkContextSessionConf",
                sparkSession,
                sparkConfigMap)
  } else {
    jsc <- get(".sparkRjsc", envir = .sparkREnv)
    sparkSession <- callJStatic("org.apache.spark.sql.api.r.SQLUtils",
                                "getOrCreateSparkSession",
                                jsc,
                                sparkConfigMap,
                                enableHiveSupport)
    assign(".sparkRsession", sparkSession, envir = .sparkREnv)
  }

  # Check if version number of SparkSession matches version number of SparkR package
  jvmVersion <- callJMethod(sparkSession, "version")
  # Remove -SNAPSHOT from jvm versions
  jvmVersionStrip <- gsub("-SNAPSHOT", "", jvmVersion, fixed = TRUE)
  rPackageVersion <- paste0(packageVersion("SparkR"))

  if (jvmVersionStrip != rPackageVersion) {
    warning("Version mismatch between Spark JVM and SparkR package. ",
            "JVM version was ", jvmVersion,
            ", while R package version was ", rPackageVersion)
  }

  sparkSession
}

#' Get the URL of the SparkUI instance for the current active SparkSession
#'
#' Get the URL of the SparkUI instance for the current active SparkSession.
#'
#' @return the SparkUI URL, or NA if it is disabled, or not started.
#' @rdname sparkR.uiWebUrl
#' @name sparkR.uiWebUrl
#' @examples
#'\dontrun{
#' sparkR.session()
#' url <- sparkR.uiWebUrl()
#' }
#' @note sparkR.uiWebUrl since 2.1.1
sparkR.uiWebUrl <- function() {
  sc <- sparkR.callJMethod(getSparkContext(), "sc")
  u <- callJMethod(sc, "uiWebUrl")
  if (callJMethod(u, "isDefined")) {
    callJMethod(u, "get")
  } else {
    NA
  }
}

#' Assigns a group ID to all the jobs started by this thread until the group ID is set to a
#' different value or cleared.
#'
#' @param groupId the ID to be assigned to job groups.
#' @param description description for the job group ID.
#' @param interruptOnCancel flag to indicate if the job is interrupted on job cancellation.
#' @rdname setJobGroup
#' @name setJobGroup
#' @examples
#'\dontrun{
#' sparkR.session()
#' setJobGroup("myJobGroup", "My job group description", TRUE)
#'}
#' @note setJobGroup since 1.5.0
setJobGroup <- function(groupId, description, interruptOnCancel) {
  sc <- getSparkContext()
  invisible(callJMethod(sc, "setJobGroup", groupId, description, interruptOnCancel))
}

#' Clear current job group ID and its description
#'
#' @rdname clearJobGroup
#' @name clearJobGroup
#' @examples
#'\dontrun{
#' sparkR.session()
#' clearJobGroup()
#'}
#' @note clearJobGroup since 1.5.0
clearJobGroup <- function() {
  sc <- getSparkContext()
  invisible(callJMethod(sc, "clearJobGroup"))
}

#' Cancel active jobs for the specified group
#'
#' @param groupId the ID of job group to be cancelled
#' @rdname cancelJobGroup
#' @name cancelJobGroup
#' @examples
#'\dontrun{
#' sparkR.session()
#' cancelJobGroup("myJobGroup")
#'}
#' @note cancelJobGroup since 1.5.0
cancelJobGroup <- function(groupId) {
  sc <- getSparkContext()
  invisible(callJMethod(sc, "cancelJobGroup", groupId))
}

#' Set a human readable description of the current job.
#'
#' Set a description that is shown as a job description in UI.
#'
#' @param value The job description of the current job.
#' @rdname setJobDescription
#' @name setJobDescription
#' @examples
#'\dontrun{
#' setJobDescription("This is an example job.")
#'}
#' @note setJobDescription since 2.3.0
setJobDescription <- function(value) {
  if (!is.null(value)) {
    value <- as.character(value)
  }
  sc <- getSparkContext()
  invisible(callJMethod(sc, "setJobDescription", value))
}

#' Set a local property that affects jobs submitted from this thread, such as the
#' Spark fair scheduler pool.
#'
#' @param key The key for a local property.
#' @param value The value for a local property.
#' @rdname setLocalProperty
#' @name setLocalProperty
#' @examples
#'\dontrun{
#' setLocalProperty("spark.scheduler.pool", "poolA")
#'}
#' @note setLocalProperty since 2.3.0
setLocalProperty <- function(key, value) {
  if (is.null(key) || is.na(key)) {
    stop("key should not be NULL or NA.")
  }
  if (!is.null(value)) {
    value <- as.character(value)
  }
  sc <- getSparkContext()
  invisible(callJMethod(sc, "setLocalProperty", as.character(key), value))
}

#' Get a local property set in this thread, or \code{NULL} if it is missing. See
#' \code{setLocalProperty}.
#'
#' @param key The key for a local property.
#' @rdname getLocalProperty
#' @name getLocalProperty
#' @examples
#'\dontrun{
#' getLocalProperty("spark.scheduler.pool")
#'}
#' @note getLocalProperty since 2.3.0
getLocalProperty <- function(key) {
  if (is.null(key) || is.na(key)) {
    stop("key should not be NULL or NA.")
  }
  sc <- getSparkContext()
  callJMethod(sc, "getLocalProperty", as.character(key))
}

sparkConfToSubmitOps <- new.env()
sparkConfToSubmitOps[["spark.driver.memory"]]           <- "--driver-memory"
sparkConfToSubmitOps[["spark.driver.extraClassPath"]]   <- "--driver-class-path"
sparkConfToSubmitOps[["spark.driver.extraJavaOptions"]] <- "--driver-java-options"
sparkConfToSubmitOps[["spark.driver.extraLibraryPath"]] <- "--driver-library-path"
sparkConfToSubmitOps[["spark.master"]] <- "--master"
sparkConfToSubmitOps[["spark.yarn.keytab"]] <- "--keytab"
sparkConfToSubmitOps[["spark.yarn.principal"]] <- "--principal"
sparkConfToSubmitOps[["spark.kerberos.keytab"]] <- "--keytab"
sparkConfToSubmitOps[["spark.kerberos.principal"]] <- "--principal"


# Utility function that returns Spark Submit arguments as a string
#
# A few Spark Application and Runtime environment properties cannot take effect after driver
# JVM has started, as documented in:
# http://spark.apache.org/docs/latest/configuration.html#application-properties
# When starting SparkR without using spark-submit, for example, from Rstudio, add them to
# spark-submit commandline if not already set in SPARKR_SUBMIT_ARGS so that they can be effective.
getClientModeSparkSubmitOpts <- function(submitOps, sparkEnvirMap) {
  envirToOps <- lapply(ls(sparkConfToSubmitOps), function(conf) {
    opsValue <- sparkEnvirMap[[conf]]
    # process only if --option is not already specified
    if (!is.null(opsValue) &&
        nchar(opsValue) > 1 &&
        !grepl(sparkConfToSubmitOps[[conf]], submitOps, fixed = TRUE)) {
      # put "" around value in case it has spaces
      paste0(sparkConfToSubmitOps[[conf]], " \"", opsValue, "\" ")
    } else {
      ""
    }
  })
  # --option must be before the application class "sparkr-shell" in submitOps
  paste0(paste0(envirToOps, collapse = ""), submitOps)
}

# Utility function that handles sparkJars argument, and normalize paths
processSparkJars <- function(jars) {
  splittedJars <- splitString(jars)
  if (length(splittedJars) > length(jars)) {
    warning("sparkJars as a comma-separated string is deprecated, use character vector instead")
  }
  normalized <- suppressWarnings(normalizePath(splittedJars))
  normalized
}

# Utility function that handles sparkPackages argument
processSparkPackages <- function(packages) {
  splittedPackages <- splitString(packages)
  if (length(splittedPackages) > length(packages)) {
    warning("sparkPackages as a comma-separated string is deprecated, use character vector instead")
  }
  splittedPackages
}

# Utility function that checks and install Spark to local folder if not found
#
# Installation will not be triggered if it's called from sparkR shell
# or if the master url is not local
#
# @param sparkHome directory to find Spark package.
# @param master the Spark master URL, used to check local or remote mode.
# @param deployMode whether to deploy your driver on the worker nodes (cluster)
#        or locally as an external client (client).
# @return NULL if no need to update sparkHome, and new sparkHome otherwise.
sparkCheckInstall <- function(sparkHome, master, deployMode) {
  if (!isSparkRShell()) {
    if (!is.na(file.info(sparkHome)$isdir)) {
      message("Spark package found in SPARK_HOME: ", sparkHome)
      NULL
    } else {
      if (interactive() || isMasterLocal(master)) {
        message("Spark not found in SPARK_HOME: ", sparkHome)
        packageLocalDir <- install.spark()
        packageLocalDir
      } else if (isClientMode(master) || deployMode == "client") {
        msg <- paste0("Spark not found in SPARK_HOME: ",
                      sparkHome, "\n", installInstruction("remote"))
        stop(msg)
      } else {
        NULL
      }
    }
  } else {
    NULL
  }
}

# Utility function for sending auth data over a socket and checking the server's reply.
doServerAuth <- function(con, authSecret) {
  if (nchar(authSecret) == 0) {
    stop("Auth secret not provided.")
  }
  writeString(con, authSecret)
  flush(con)
  reply <- readString(con)
  if (reply != "ok") {
    close(con)
    stop("Unexpected reply from server.")
  }
}

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SparkR documentation built on June 3, 2021, 5:05 p.m.