Windows Server 2003 Networking Recipes

最新推荐文章于 2025-07-17 19:18:54 发布
最新推荐文章于 2025-07-17 19:18:54 发布
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分类专栏： Windows 2003 文章标签： networking windows server protocols reference network
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Windows Server 2003 Networking Recipes is ideal for network managers and Windows Server 2003 system administrators responsible for setting up and running computers and networks. Think of this book as the comprehensive, task-based guide to installing, deploying, and configuring the various networking protocols and services supported by Windows Server 2003--and the only book you'll need.

You'll find hundreds of quick reference solutions. And the featured recipes are all based on the first-hand experiences of the authors. You can rest assured that this book is written by a team of leading experts in Windows administration.


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op3.2\jars\RoaringBitmap-0.9.0.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\scala-collection-compat_2.12-2.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\scala-compiler-2.12.10.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\scala-library-2.12.10.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\scala-parser-combinators_2.12-1.1.2.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\scala-reflect-2.12.10.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\scala-xml_2.12-1.2.0.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\shapeless_2.12-2.3.3.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\shims-0.9.0.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\slf4j-api-1.7.30.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\slf4j-log4j12-1.7.30.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\snakeyaml-1.24.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\snappy-java-1.1.8.2.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-catalyst_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-core_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-graphx_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-hive-thriftserver_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-hive_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-kubernetes_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-kvstore_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-launcher_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-mesos_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-mllib-local_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-mllib_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-network-common_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-network-shuffle_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-repl_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-sketch_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-sql_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-streaming_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-tags_2.12-3.1.1-tests.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-tags_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-unsafe_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spark-yarn_2.12-3.1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spire-macros_2.12-0.17.0-M1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spire-platform_2.12-0.17.0-M1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spire-util_2.12-0.17.0-M1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\spire_2.12-0.17.0-M1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\ST4-4.0.4.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\stax-api-1.0.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\stax2-api-3.1.4.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\stream-2.9.6.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\super-csv-2.2.0.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\threeten-extra-1.5.0.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\token-provider-1.0.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\transaction-api-1.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\univocity-parsers-2.9.1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\velocity-1.5.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\woodstox-core-5.0.3.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\xbean-asm7-shaded-4.15.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\xz-1.5.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\zjsonpatch-0.3.0.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\zookeeper-3.4.14.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\zstd-jni-1.4.8-1.jar;D:\spark\spark-3.1.1-bin-hadoop3.2\jars\arrow-vector-2.0.0.jar" car.LoadModelRideHailing Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties 25/06/08 17:05:07 INFO SparkContext: Running Spark version 3.1.1 25/06/08 17:05:07 INFO ResourceUtils: ============================================================== 25/06/08 17:05:07 INFO ResourceUtils: No custom resources configured for spark.driver. 25/06/08 17:05:07 INFO ResourceUtils: ============================================================== 25/06/08 17:05:07 INFO SparkContext: Submitted application: LoadModelRideHailing 25/06/08 17:05:07 INFO ResourceProfile: Default ResourceProfile created, executor resources: Map(cores -> name: cores, amount: 1, script: , vendor: , memory -> name: memory, amount: 1024, script: , vendor: , offHeap -> name: offHeap, amount: 0, script: , vendor: ), task resources: Map(cpus -> name: cpus, amount: 1.0) 25/06/08 17:05:07 INFO ResourceProfile: Limiting resource is cpu 25/06/08 17:05:07 INFO ResourceProfileManager: Added ResourceProfile id: 0 25/06/08 17:05:07 INFO SecurityManager: Changing view acls to: wyatt 25/06/08 17:05:07 INFO SecurityManager: Changing modify acls to: wyatt 25/06/08 17:05:07 INFO SecurityManager: Changing view acls groups to: 25/06/08 17:05:07 INFO SecurityManager: Changing modify acls groups to: 25/06/08 17:05:07 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(wyatt); groups with view permissions: Set(); users with modify permissions: Set(wyatt); groups with modify permissions: Set() 25/06/08 17:05:07 INFO Utils: Successfully started service 'sparkDriver' on port 59361. 25/06/08 17:05:07 INFO SparkEnv: Registering MapOutputTracker 25/06/08 17:05:07 INFO SparkEnv: Registering BlockManagerMaster 25/06/08 17:05:08 INFO BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information 25/06/08 17:05:08 INFO BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up 25/06/08 17:05:08 INFO SparkEnv: Registering BlockManagerMasterHeartbeat 25/06/08 17:05:08 INFO DiskBlockManager: Created local directory at C:\Users\wyatt\AppData\Local\Temp\blockmgr-8fe065e2-024c-4e2f-8662-45d2fe3de444 25/06/08 17:05:08 INFO MemoryStore: MemoryStore started with capacity 1899.0 MiB 25/06/08 17:05:08 INFO SparkEnv: Registering OutputCommitCoordinator 25/06/08 17:05:08 INFO Utils: Successfully started service 'SparkUI' on port 4040. 25/06/08 17:05:08 INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at http://windows10.microdone.cn:4040 25/06/08 17:05:08 INFO Executor: Starting executor ID driver on host windows10.microdone.cn 25/06/08 17:05:08 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 59392. 25/06/08 17:05:08 INFO NettyBlockTransferService: Server created on windows10.microdone.cn:59392 25/06/08 17:05:08 INFO BlockManager: Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy 25/06/08 17:05:08 INFO BlockManagerMaster: Registering BlockManager BlockManagerId(driver, windows10.microdone.cn, 59392, None) 25/06/08 17:05:08 INFO BlockManagerMasterEndpoint: Registering block manager windows10.microdone.cn:59392 with 1899.0 MiB RAM, BlockManagerId(driver, windows10.microdone.cn, 59392, None) 25/06/08 17:05:08 INFO BlockManagerMaster: Registered BlockManager BlockManagerId(driver, windows10.microdone.cn, 59392, None) 25/06/08 17:05:08 INFO BlockManager: Initialized BlockManager: BlockManagerId(driver, windows10.microdone.cn, 59392, None) Exception in thread "main" java.lang.IllegalArgumentException: 测试数据中不包含 features 列，请检查数据！ at car.LoadModelRideHailing$.main(LoadModelRideHailing.scala:23) at car.LoadModelRideHailing.main(LoadModelRideHailing.scala) 进程已结束，退出代码为 1 package car import org.apache.spark.ml.classification.{LogisticRegressionModel, RandomForestClassificationModel} import org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator import org.apache.spark.sql.{SparkSession, functions => F} object LoadModelRideHailing { def main(args: Array[String]): Unit = { val spark = SparkSession.builder() .master("local[3]") .appName("LoadModelRideHailing") .getOrCreate() spark.sparkContext.setLogLevel("Error") // 使用经过特征工程处理后的测试数据 val TestData = spark.read.option("header", "true").csv("C:\\Users\\wyatt\\Documents\\ride_hailing_test_data.csv") // 将 label 列转换为数值类型 val testDataWithNumericLabel = TestData.withColumn("label", F.col("label").cast("double")) // 检查 features 列是否存在 if (!testDataWithNumericLabel.columns.contains("features")) { throw new IllegalArgumentException("测试数据中不包含 features 列，请检查数据！") } // 修正后的模型路径（确保文件夹存在且包含元数据） val LogisticModel = LogisticRegressionModel.load("C:\\Users\\wyatt\\Documents\\ride_hailing_logistic_model") // 示例路径 val LogisticPre = LogisticModel.transform(testDataWithNumericLabel) val LogisticAcc = new MulticlassClassificationEvaluator() .setLabelCol("label") .setPredictionCol("prediction") .setMetricName("accuracy") .evaluate(LogisticPre) println("逻辑回归模型后期数据准确率：" + LogisticAcc) // 随机森林模型路径同步修正 val RandomForest = RandomForestClassificationModel.load("C:\\Users\\wyatt\\Documents\\ride_hailing_random_forest_model") // 示例路径 val RandomForestPre = RandomForest.transform(testDataWithNumericLabel) val RandomForestAcc = new MulticlassClassificationEvaluator() .setLabelCol("label") .setPredictionCol("prediction") .setMetricName("accuracy") .evaluate(RandomForestPre) println("随机森林模型后期数据准确率：" + RandomForestAcc) spark.stop() } }
06-09
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