1. 2. 3. 4. 5. 6. 7. 8. 9. 步骤3: 加载数据集 加载一个数据集,这里我们使用一个简单的CSV文件作为例子。 # 加载数据集data_path="data/example.csv"# 数据的位置df=spark.read.csv(data_path,header=True,inferSchema=True)# 展示数据结构df.show() 1. 2. 3. 4. 5. 6. 步骤4: 应用正则...
public static void main(String[] args) { String path = JavaWordCount.class.getClassLoader().getResource("words.txt").getPath(); SparkSession spark = SparkSession.builder().appName("JavaWordCount").getOrCreate(); JavaRDD<String> lines = spark.read().textFile(path).javaRDD(); JavaRDD<S...
from pyspark.sql import SparkSession spark = SparkSession.builder.getOrCreate() files = spark.read.text("path/to/files/*.txt") 在这个例子中,"path/to/files/*.txt"是一个glob模式,它将匹配所有以".txt"结尾的文件。 glob在Spark中的应用场景非常广泛。它可以用于数据预处理、数据清洗、数据分析等各...
这是一个简单的例子: // In Scala val strings = spark .read.text("/databricks-datasets/learning-spark-v2/SPARK_README.md") val filtered = strings.filter($"value".contains("Spark")) filtered.count() # In Python strings = spark .read.text("/databricks-datasets/learning-spark-v2/SPARK_READ...
"]+)"" ""([^""]+)"".*"; var spark = SparkSession.Builder().AppName("LogReader").GetOrCreate(); var dataFrame = spark.Read().Text("log.txt"); dataFrame .WithColumn("user", RegexpExtract(dataFrame["value"], regex, 3)) .WithColumn("bytes", RegexpExtract(dataFrame["value"], ...
读取JSON文件并创建DataFrame:df = spark.read.json("path/to/json/file.json")其中,"path/to/json/file.json"是JSON文件的路径。 查看DataFrame的结构:df.printSchema()这将显示DataFrame的列名和数据类型。 提取键和值:df.select("key").show() df.select("value").show()这将分别显示DataFrame中"key"列...
Like的正则表达式(Regex) # 以Parquet格式读取源表sales_table = spark.read.parquet("./data/sales_parquet")''' SELECT * FROM sales_table WHERE bill_raw_text RLIKE '(ab[cd]{2,4})|(aa[abcde]{1,2})' '''sales_table_execution_plan = sales_table.where( ...
Operation category READ is not supported in state standby 解决方案: 查看执行Spark计算的是否处于standby状态, 用浏览器访问该主机:http://m1:50070, 如果处于standby状态, 则不可在处于StandBy机器运行spark计算,应切执行Spark计算的主机从Standby状态切换到Active状态 ...
read.json(path).as[Person] peopleDS.show() // +---+---+ // | age| name| // +---+---+ // |null|Michael| // | 30| Andy| // | 19| Justin| // +---+---+ 完整示例代码可在Spark存储库的“examples/src/main/scala/org/apache/spark/examples/sql/SparkSQLExample.scala”中...
spark.sql.redaction.string.regex Regex to decide which parts of strings produced by Spark contain sensitive information. When this regex matches a string part, that string part is replaced by a dummy value. This is currently used to redact the output of SQL explain commands. When this conf is...