[SPARK-33346][CORE][SQL][MLLIB][DSTREAM][K8S] Change the never changed 'var' to 'val'
### What changes were proposed in this pull request? Some local variables are declared as `var`, but they are never reassigned and should be declared as `val`, so this pr turn these from `var` to `val` except for `mockito` related cases. ### Why are the changes needed? Use `val` instead of `var` when possible. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Pass the Jenkins or GitHub Action Closes #31142 from LuciferYang/SPARK-33346. Authored-by: yangjie01 <yangjie01@baidu.com> Signed-off-by: Sean Owen <srowen@gmail.com>
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9e33d49b5b
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@ -240,7 +240,7 @@ private[spark] class SparkSubmit extends Logging {
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}
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// Set the deploy mode; default is client mode
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var deployMode: Int = args.deployMode match {
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val deployMode: Int = args.deployMode match {
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case "client" | null => CLIENT
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case "cluster" => CLUSTER
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case _ =>
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@ -125,7 +125,7 @@ private[spark] class TaskSetManager(
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val weight = 1
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val minShare = 0
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var priority = taskSet.priority
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var stageId = taskSet.stageId
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val stageId = taskSet.stageId
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val name = "TaskSet_" + taskSet.id
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var parent: Pool = null
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private var totalResultSize = 0L
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@ -430,7 +430,7 @@ private class LiveStage extends LiveEntity {
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// Used for cleanup of tasks after they reach the configured limit. Not written to the store.
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@volatile var cleaning = false
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var savedTasks = new AtomicInteger(0)
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val savedTasks = new AtomicInteger(0)
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def executorSummary(executorId: String): LiveExecutorStageSummary = {
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executorSummaries.getOrElseUpdate(executorId,
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@ -37,13 +37,13 @@ private[spark] class MedianHeap(implicit val ord: Ordering[Double]) {
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* Stores all the numbers less than the current median in a smallerHalf,
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* i.e median is the maximum, at the root.
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*/
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private[this] var smallerHalf = PriorityQueue.empty[Double](ord)
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private[this] val smallerHalf = PriorityQueue.empty[Double](ord)
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/**
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* Stores all the numbers greater than the current median in a largerHalf,
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* i.e median is the minimum, at the root.
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*/
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private[this] var largerHalf = PriorityQueue.empty[Double](ord.reverse)
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private[this] val largerHalf = PriorityQueue.empty[Double](ord.reverse)
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def isEmpty(): Boolean = {
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smallerHalf.isEmpty && largerHalf.isEmpty
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@ -27,7 +27,7 @@ trait SharedSparkContext extends BeforeAndAfterAll with BeforeAndAfterEach { sel
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def sc: SparkContext = _sc
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var conf = new SparkConf(false)
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val conf = new SparkConf(false)
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/**
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* Initialize the [[SparkContext]]. Generally, this is just called from beforeAll; however, in
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@ -461,7 +461,7 @@ class SparkConfSuite extends SparkFunSuite with LocalSparkContext with ResetSyst
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val conf = new SparkConf()
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conf.set(TASK_GPU_ID.amountConf, "2")
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conf.set(TASK_FPGA_ID.amountConf, "0")
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var taskResourceRequirement =
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val taskResourceRequirement =
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parseResourceRequirements(conf, SPARK_TASK_PREFIX)
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.map(req => (req.resourceName, req.amount)).toMap
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@ -939,7 +939,7 @@ class SparkContextSuite extends SparkFunSuite with LocalSparkContext with Eventu
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.setAppName("test-cluster")
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conf.set(TASK_GPU_ID.amountConf, "1")
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var error = intercept[SparkException] {
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val error = intercept[SparkException] {
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sc = new SparkContext(conf)
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}.getMessage()
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@ -954,7 +954,7 @@ class SparkContextSuite extends SparkFunSuite with LocalSparkContext with Eventu
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conf.set(TASK_GPU_ID.amountConf, "2")
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conf.set(EXECUTOR_GPU_ID.amountConf, "1")
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var error = intercept[SparkException] {
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val error = intercept[SparkException] {
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sc = new SparkContext(conf)
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}.getMessage()
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@ -970,7 +970,7 @@ class SparkContextSuite extends SparkFunSuite with LocalSparkContext with Eventu
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conf.set(TASK_GPU_ID.amountConf, "2")
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conf.set(EXECUTOR_GPU_ID.amountConf, "4")
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var error = intercept[SparkException] {
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val error = intercept[SparkException] {
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sc = new SparkContext(conf)
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}.getMessage()
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@ -55,7 +55,7 @@ class ApplicationCacheSuite extends SparkFunSuite with Logging with MockitoSugar
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var getAppUICount = 0L
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var attachCount = 0L
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var detachCount = 0L
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var updateProbeCount = 0L
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val updateProbeCount = 0L
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override def getAppUI(appId: String, attemptId: Option[String]): Option[LoadedAppUI] = {
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logDebug(s"getAppUI($appId, $attemptId)")
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@ -216,7 +216,7 @@ class SingleFileEventLogFileReaderSuite extends EventLogFileReadersSuite {
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Utils.tryWithResource(new ZipInputStream(
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new ByteArrayInputStream(underlyingStream.toByteArray))) { is =>
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var entry = is.getNextEntry
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val entry = is.getNextEntry
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assert(entry != null)
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val actual = new String(ByteStreams.toByteArray(is), StandardCharsets.UTF_8)
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val expected = Files.toString(new File(logPath.toString), StandardCharsets.UTF_8)
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@ -58,7 +58,7 @@ class MockWorker(master: RpcEndpointRef, conf: SparkConf = new SparkConf) extend
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val id = seq.toString
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override val rpcEnv: RpcEnv = RpcEnv.create("worker", "localhost", seq,
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conf, new SecurityManager(conf))
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var apps = new mutable.HashMap[String, String]()
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val apps = new mutable.HashMap[String, String]()
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val driverIdToAppId = new mutable.HashMap[String, String]()
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def newDriver(driverId: String): RpcEndpointRef = {
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val name = s"driver_${drivers.size}"
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@ -61,7 +61,7 @@ class CoarseGrainedExecutorBackendSuite extends SparkFunSuite
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val testResourceArgs: JObject = ("" -> "")
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val ja = JArray(List(testResourceArgs))
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val f1 = createTempJsonFile(tmpDir, "resources", ja)
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var error = intercept[SparkException] {
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val error = intercept[SparkException] {
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val parsedResources = backend.parseOrFindResources(Some(f1))
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}.getMessage()
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@ -146,7 +146,7 @@ class CoarseGrainedExecutorBackendSuite extends SparkFunSuite
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val ja = Extraction.decompose(Seq(gpuArgs))
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val f1 = createTempJsonFile(tmpDir, "resources", ja)
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var error = intercept[IllegalArgumentException] {
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val error = intercept[IllegalArgumentException] {
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val parsedResources = backend.parseOrFindResources(Some(f1))
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}.getMessage()
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@ -160,7 +160,7 @@ class CoarseGrainedExecutorBackendSuite extends SparkFunSuite
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val ja = Extraction.decompose(Seq(fpga))
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val f1 = createTempJsonFile(tmpDir, "resources", ja)
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var error = intercept[SparkException] {
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val error = intercept[SparkException] {
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val parsedResources = backend.parseOrFindResources(Some(f1))
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}.getMessage()
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@ -199,7 +199,7 @@ class CoarseGrainedExecutorBackendSuite extends SparkFunSuite
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val ja = Extraction.decompose(Seq(gpuArgs))
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val f1 = createTempJsonFile(tmpDir, "resources", ja)
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var error = intercept[IllegalArgumentException] {
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val error = intercept[IllegalArgumentException] {
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val parsedResources = backend.parseOrFindResources(Some(f1))
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}.getMessage()
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@ -110,7 +110,7 @@ class ResourceProfileManagerSuite extends SparkFunSuite {
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val gpuExecReq =
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new ExecutorResourceRequests().resource("gpu", 2, "someScript")
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val immrprof = rprof.require(gpuExecReq).build
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var error = intercept[SparkException] {
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val error = intercept[SparkException] {
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rpmanager.isSupported(immrprof)
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}.getMessage()
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@ -178,7 +178,7 @@ class ResourceUtilsSuite extends SparkFunSuite
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test("list resource ids") {
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val conf = new SparkConf
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conf.set(DRIVER_GPU_ID.amountConf, "2")
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var resources = listResourceIds(conf, SPARK_DRIVER_PREFIX)
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val resources = listResourceIds(conf, SPARK_DRIVER_PREFIX)
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assert(resources.size === 1, "should only have GPU for resource")
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assert(resources(0).resourceName == GPU, "name should be gpu")
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@ -99,8 +99,8 @@ class CoarseGrainedSchedulerBackendSuite extends SparkFunSuite with LocalSparkCo
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Thread.sleep(5000)
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iter
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}
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var taskStarted = new AtomicBoolean(false)
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var taskEnded = new AtomicBoolean(false)
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val taskStarted = new AtomicBoolean(false)
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val taskEnded = new AtomicBoolean(false)
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val listener = new SparkListener() {
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override def onTaskStart(taskStart: SparkListenerTaskStart): Unit = {
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taskStarted.set(true)
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@ -239,11 +239,11 @@ class CoarseGrainedSchedulerBackendSuite extends SparkFunSuite with LocalSparkCo
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var execResources = backend.getExecutorAvailableResources("1")
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assert(execResources(GPU).availableAddrs.sorted === Array("0", "1", "3"))
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var exec3ResourceProfileId = backend.getExecutorResourceProfileId("3")
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val exec3ResourceProfileId = backend.getExecutorResourceProfileId("3")
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assert(exec3ResourceProfileId === rp.id)
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val taskResources = Map(GPU -> new ResourceInformation(GPU, Array("0")))
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var taskDescs: Seq[Seq[TaskDescription]] = Seq(Seq(new TaskDescription(1, 0, "1",
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val taskDescs: Seq[Seq[TaskDescription]] = Seq(Seq(new TaskDescription(1, 0, "1",
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"t1", 0, 1, mutable.Map.empty[String, Long],
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mutable.Map.empty[String, Long], mutable.Map.empty[String, Long],
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new Properties(), taskResources, bytebuffer)))
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@ -3336,7 +3336,7 @@ class DAGSchedulerSuite extends SparkFunSuite with TempLocalSparkContext with Ti
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val ereqs3 = new ExecutorResourceRequests().cores(3)
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val treqs3 = new TaskResourceRequests().cpus(2)
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val rp3 = new ResourceProfile(ereqs3.requests, treqs3.requests)
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var mergedRp = scheduler.mergeResourceProfilesForStage(HashSet(rp1, rp2, rp3))
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val mergedRp = scheduler.mergeResourceProfilesForStage(HashSet(rp1, rp2, rp3))
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assert(mergedRp.getTaskCpus.get == 2)
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assert(mergedRp.getExecutorCores.get == 4)
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@ -1007,7 +1007,7 @@ class TaskSchedulerImplSuite extends SparkFunSuite with LocalSparkContext with B
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val tsm = stageToMockTaskSetManager(0)
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// submit an offer with one executor
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var taskAttempts = taskScheduler.resourceOffers(IndexedSeq(
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val taskAttempts = taskScheduler.resourceOffers(IndexedSeq(
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WorkerOffer("executor0", "host0", 1)
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)).flatten
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@ -1763,7 +1763,7 @@ class TaskSchedulerImplSuite extends SparkFunSuite with LocalSparkContext with B
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taskScheduler.submitTasks(taskSet)
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// Launch tasks on executor that satisfies resource requirements.
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var taskDescriptions = taskScheduler.resourceOffers(singleCoreWorkerOffers).flatten
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val taskDescriptions = taskScheduler.resourceOffers(singleCoreWorkerOffers).flatten
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assert(3 === taskDescriptions.length)
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assert(!failedTaskSet)
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assert(ArrayBuffer("0") === taskDescriptions(0).resources.get(GPU).get.addresses)
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@ -54,14 +54,14 @@ class CryptoStreamUtilsSuite extends SparkFunSuite {
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test("shuffle encryption key length should be 128 by default") {
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val conf = createConf()
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var key = CryptoStreamUtils.createKey(conf)
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val key = CryptoStreamUtils.createKey(conf)
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val actual = key.length * (java.lang.Byte.SIZE)
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assert(actual === 128)
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}
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test("create 256-bit key") {
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val conf = createConf(IO_ENCRYPTION_KEY_SIZE_BITS.key -> "256")
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var key = CryptoStreamUtils.createKey(conf)
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val key = CryptoStreamUtils.createKey(conf)
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val actual = key.length * (java.lang.Byte.SIZE)
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assert(actual === 256)
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}
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@ -35,8 +35,8 @@ class ElementTrackingStoreSuite extends SparkFunSuite with Eventually {
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val tracking = new ElementTrackingStore(store, new SparkConf()
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.set(ASYNC_TRACKING_ENABLED, true))
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var done = new AtomicBoolean(false)
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var type1 = new AtomicInteger(0)
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val done = new AtomicBoolean(false)
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val type1 = new AtomicInteger(0)
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var queued0: WriteQueueResult = null
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var queued1: WriteQueueResult = null
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var queued2: WriteQueueResult = null
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@ -37,7 +37,7 @@ class FlatmapIteratorSuite extends SparkFunSuite with LocalSparkContext {
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val expand_size = 100
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val data = sc.parallelize((1 to 5).toSeq).
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flatMap( x => Stream.range(0, expand_size))
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var persisted = data.persist(StorageLevel.DISK_ONLY)
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val persisted = data.persist(StorageLevel.DISK_ONLY)
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assert(persisted.count()===500)
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assert(persisted.filter(_==1).count()===5)
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}
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@ -48,7 +48,7 @@ class FlatmapIteratorSuite extends SparkFunSuite with LocalSparkContext {
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val expand_size = 100
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val data = sc.parallelize((1 to 5).toSeq).
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flatMap(x => Stream.range(0, expand_size))
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var persisted = data.persist(StorageLevel.MEMORY_ONLY)
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val persisted = data.persist(StorageLevel.MEMORY_ONLY)
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assert(persisted.count()===500)
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assert(persisted.filter(_==1).count()===5)
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}
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@ -39,7 +39,7 @@ class MemoryStoreSuite
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with BeforeAndAfterEach
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with ResetSystemProperties {
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var conf: SparkConf = new SparkConf(false)
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val conf: SparkConf = new SparkConf(false)
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.set(STORAGE_UNROLL_MEMORY_THRESHOLD, 512L)
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// Reuse a serializer across tests to avoid creating a new thread-local buffer on each test
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@ -147,7 +147,7 @@ object TestObject {
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}
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class TestClass extends Serializable {
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var x = 5
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val x = 5
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def getX: Int = x
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@ -179,7 +179,7 @@ class TestClassWithoutFieldAccess {
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def run(): Int = {
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var nonSer2 = new NonSerializable
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var x = 5
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val x = 5
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withSpark(new SparkContext("local", "test")) { sc =>
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val nums = sc.parallelize(Array(1, 2, 3, 4))
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nums.map(_ + x).reduce(_ + _)
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@ -218,10 +218,10 @@ object TestObjectWithNesting {
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var answer = 0
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withSpark(new SparkContext("local", "test")) { sc =>
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val nums = sc.parallelize(Array(1, 2, 3, 4))
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var y = 1
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val y = 1
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for (i <- 1 to 4) {
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var nonSer2 = new NonSerializable
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var x = i
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val x = i
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answer += nums.map(_ + x + y).reduce(_ + _)
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}
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answer
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@ -239,7 +239,7 @@ class TestClassWithNesting(val y: Int) extends Serializable {
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val nums = sc.parallelize(Array(1, 2, 3, 4))
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for (i <- 1 to 4) {
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var nonSer2 = new NonSerializable
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var x = i
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val x = i
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answer += nums.map(_ + x + getY).reduce(_ + _)
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}
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answer
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@ -339,7 +339,7 @@ private object TestUserClosuresActuallyCleaned {
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class TestCreateNullValue {
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var x = 5
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val x = 5
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def getX: Int = x
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@ -323,7 +323,7 @@ class RandomSamplerSuite extends SparkFunSuite with Matchers {
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RandomSampler.defaultMaxGapSamplingFraction should be (0.4)
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var d: Double = 0.0
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var sampler = new BernoulliSampler[Int](0.1)
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val sampler = new BernoulliSampler[Int](0.1)
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sampler.setSeed(rngSeed.nextLong)
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// Array iterator (indexable type)
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@ -547,7 +547,7 @@ class RandomSamplerSuite extends SparkFunSuite with Matchers {
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RandomSampler.defaultMaxGapSamplingFraction should be (0.4)
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var d: Double = 0.0
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var sampler = new PoissonSampler[Int](0.1)
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val sampler = new PoissonSampler[Int](0.1)
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sampler.setSeed(rngSeed.nextLong)
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// Array iterator (indexable type)
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@ -101,7 +101,7 @@ object LocalKMeans {
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}
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}
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var newPoints = pointStats.map {mapping =>
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val newPoints = pointStats.map { mapping =>
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(mapping._1, mapping._2._1 * (1.0 / mapping._2._2))}
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tempDist = 0.0
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@ -236,7 +236,7 @@ class KafkaRDDSuite extends SparkFunSuite with BeforeAndAfterAll {
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// this is the "lots of messages" case
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kafkaTestUtils.sendMessages(topic, sent)
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var sentCount = sent.values.sum
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val sentCount = sent.values.sum
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val rdd = KafkaUtils.createRDD[String, String](sc, kafkaParams,
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Array(OffsetRange(topic, 0, 0, sentCount)), preferredHosts)
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@ -67,7 +67,7 @@ private[mllib] object EigenValueDecomposition {
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// "LM" : compute the NEV largest (in magnitude) eigenvalues
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val which = "LM"
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var iparam = new Array[Int](11)
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val iparam = new Array[Int](11)
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// use exact shift in each iteration
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iparam(0) = 1
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// maximum number of Arnoldi update iterations, or the actual number of iterations on output
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@ -224,7 +224,7 @@ class PowerIterationClusteringSuite extends SparkFunSuite
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(3, 4)
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)).toDF("src", "dst").repartition(1)
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var assignments2 = new PowerIterationClustering()
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val assignments2 = new PowerIterationClustering()
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.setInitMode("random")
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.setK(2)
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.assignClusters(data2)
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@ -238,7 +238,7 @@ class PowerIterationClusteringSuite extends SparkFunSuite
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assert(Set(predictions2(0).size, predictions2(1).size) !== Set(2, 3))
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var assignments3 = new PowerIterationClustering()
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val assignments3 = new PowerIterationClustering()
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.setInitMode("degree")
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.setK(2)
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.assignClusters(data2)
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@ -219,7 +219,7 @@ private[joins] class UnsafeHashedRelation(
|
|||
var resultRow = new UnsafeRow(numFields)
|
||||
|
||||
// re-used in getWithKeyIndex()/getValueWithKeyIndex()/valuesWithKeyIndex()
|
||||
var valueRowWithKeyIndex = new ValueRowWithKeyIndex
|
||||
val valueRowWithKeyIndex = new ValueRowWithKeyIndex
|
||||
|
||||
override def get(key: InternalRow): Iterator[InternalRow] = {
|
||||
val unsafeKey = key.asInstanceOf[UnsafeRow]
|
||||
|
|
|
@ -56,7 +56,7 @@ case class ForeachWriterTable[T](
|
|||
|
||||
override def newWriteBuilder(info: LogicalWriteInfo): WriteBuilder = {
|
||||
new WriteBuilder with SupportsTruncate with SupportsStreamingUpdateAsAppend {
|
||||
private var inputSchema: StructType = info.schema()
|
||||
private val inputSchema: StructType = info.schema()
|
||||
|
||||
// Do nothing for truncate. Foreach sink is special and it just forwards all the
|
||||
// records to ForeachWriter.
|
||||
|
|
|
@ -430,8 +430,8 @@ class DataStreamReaderWriterSuite extends StreamTest with BeforeAndAfter {
|
|||
.format("org.apache.spark.sql.streaming.test")
|
||||
.load()
|
||||
|
||||
var w = df.writeStream
|
||||
var e = intercept[IllegalArgumentException](w.foreach(null))
|
||||
val w = df.writeStream
|
||||
val e = intercept[IllegalArgumentException](w.foreach(null))
|
||||
Seq("foreach", "null").foreach { s =>
|
||||
assert(e.getMessage.toLowerCase(Locale.ROOT).contains(s.toLowerCase(Locale.ROOT)))
|
||||
}
|
||||
|
@ -447,8 +447,8 @@ class DataStreamReaderWriterSuite extends StreamTest with BeforeAndAfter {
|
|||
override def process(value: Row): Unit = {}
|
||||
override def close(errorOrNull: Throwable): Unit = {}
|
||||
}
|
||||
var w = df.writeStream.partitionBy("value")
|
||||
var e = intercept[AnalysisException](w.foreach(foreachWriter).start())
|
||||
val w = df.writeStream.partitionBy("value")
|
||||
val e = intercept[AnalysisException](w.foreach(foreachWriter).start())
|
||||
Seq("foreach", "partitioning").foreach { s =>
|
||||
assert(e.getMessage.toLowerCase(Locale.ROOT).contains(s.toLowerCase(Locale.ROOT)))
|
||||
}
|
||||
|
|
|
@ -380,7 +380,7 @@ class DataFrameReaderWriterSuite extends QueryTest with SharedSparkSession with
|
|||
withTable("t") {
|
||||
sql("create table t(i int, d double) using parquet")
|
||||
// Calling `saveAsTable` to an existing table with append mode results in table insertion.
|
||||
var msg = intercept[AnalysisException] {
|
||||
val msg = intercept[AnalysisException] {
|
||||
Seq((1L, 2.0)).toDF("i", "d").write.mode("append").saveAsTable("t")
|
||||
}.getMessage
|
||||
assert(msg.contains("Cannot safely cast 'i': bigint to int"))
|
||||
|
|
|
@ -208,7 +208,7 @@ class HiveQuerySuite extends HiveComparisonTest with SQLTestUtils with BeforeAnd
|
|||
|FROM src LIMIT 1""".stripMargin)
|
||||
|
||||
test("constant null testing timestamp") {
|
||||
var r1 = sql(
|
||||
val r1 = sql(
|
||||
"""
|
||||
|SELECT IF(FALSE, CAST(NULL AS TIMESTAMP),
|
||||
|CAST('1969-12-31 16:00:01' AS TIMESTAMP)) AS COL20
|
||||
|
|
|
@ -30,7 +30,7 @@ import org.apache.spark.internal.Logging
|
|||
trait LocalStreamingContext extends BeforeAndAfterEach { self: Suite =>
|
||||
|
||||
@transient var ssc: StreamingContext = _
|
||||
@transient var stopSparkContext: Boolean = true
|
||||
@transient val stopSparkContext: Boolean = true
|
||||
|
||||
override def afterEach(): Unit = {
|
||||
try {
|
||||
|
|
|
@ -332,7 +332,7 @@ class KillingThread(ssc: StreamingContext, maxKillWaitTime: Long) extends Thread
|
|||
override def run(): Unit = {
|
||||
try {
|
||||
// If it is the first killing, then allow the first checkpoint to be created
|
||||
var minKillWaitTime = if (MasterFailureTest.killCount == 0) 5000 else 2000
|
||||
val minKillWaitTime = if (MasterFailureTest.killCount == 0) 5000 else 2000
|
||||
val killWaitTime = minKillWaitTime + math.abs(Random.nextLong % maxKillWaitTime)
|
||||
logInfo("Kill wait time = " + killWaitTime)
|
||||
Thread.sleep(killWaitTime)
|
||||
|
|
|
@ -75,7 +75,7 @@ abstract class BaseReceivedBlockHandlerSuite(enableEncryption: Boolean)
|
|||
val mapOutputTracker = new MapOutputTrackerMaster(conf, broadcastManager, true)
|
||||
val shuffleManager = new SortShuffleManager(conf)
|
||||
val serializer = new KryoSerializer(conf)
|
||||
var serializerManager = new SerializerManager(serializer, conf, encryptionKey)
|
||||
val serializerManager = new SerializerManager(serializer, conf, encryptionKey)
|
||||
val manualClock = new ManualClock
|
||||
val blockManagerSize = 10000000
|
||||
val blockManagerBuffer = new ArrayBuffer[BlockManager]()
|
||||
|
|
|
@ -203,7 +203,7 @@ private[streaming] object RateTestReceiver {
|
|||
*/
|
||||
class StoppableReceiver extends Receiver[Int](StorageLevel.MEMORY_ONLY) {
|
||||
|
||||
var receivingThreadOption: Option[Thread] = None
|
||||
val receivingThreadOption: Option[Thread] = None
|
||||
|
||||
def onStart(): Unit = {
|
||||
val thread = new Thread() {
|
||||
|
|
Loading…
Reference in a new issue