使用半結構化資料做為 VARIANT 類型的內建 Apache Spark 支援現在可在 Spark DataFrame 和 SQL 中使用。 請參閱<查詢變化資料>。公開預覽中 Delta Lake 的變化類型支援您現在可以使用 VARIANT,將半結構化資料儲存在 Delta Lake 支援的資料表中。 請參閱<Delta Lake 中的變化支援>。
createDataFrame(data, schema=None, samplingRatio=None, verifySchema=True) 3,从SQL查询中创建DataFrame 从一个给定的SQL查询或Table中获取DataFrame,举个例子: df.createOrReplaceTempView("table1")#use SQL query to fetch datadf2 = spark.sql("SELECT field1 AS f1, field2 as f2 from table1")#use ...
createDataFrame(data, schema=None, samplingRatio=None, verifySchema=True) 1. 3,从SQL查询中创建DataFrame 从一个给定的SQL查询或Table中获取DataFrame,举个例子: df.createOrReplaceTempView("table1") #use SQL query to fetch data df2 = spark.sql("SELECT field1 AS f1, field2 as f2 from table1"...
.option/.options下列方法: DataFrameReader DataFrameWriter DataStreamReader DataStreamWriter 下列內建函式: from_xml to_xml schema_of_xml OPTIONS CREATE TABLE USING DATA_SOURCE 的 子句如需選項清單,請參閱 自動載入器選項。XSD 支援您可以選擇性地驗證 XML 架構定義 (XSD) 的每個資料列層級 XML 記錄。
inferSchema If true, attempts to infer an appropriate type for each resulting DataFrame column. If false, all resulting columns are of string type. Default:true. XML built-in functions ignore this option. read columnNameOfCorruptRecord Allows renaming the new field that contains a malformed string...
createDataFrame(sc.emptyRDD(), schema) or this: sc.parallelize([1, 2, 3]) [back to top] not-supported Installing eggs is no longer supported on Databricks 14.0 or higher. [back to top] notebook-run-cannot-compute-value Path for dbutils.notebook.run cannot be computed and requires ...
df = spark.sql('SELECT approx_top_k(col, 10, 100) FROM VALUES (0), (1), (1), (2), (2), (2) AS tab(col)') display(df) Python コピー import pyspark.sql.functions as F df = spark.createDataFrame([ (0,), (1,), (1,), (2,), (2,), (2,) ]).select(F.expr(...
load() // Load data from an Azure Synapse query. val df: DataFrame = spark.read .format("com.databricks.spark.sqldw") .option("url", "jdbc:sqlserver://<the-rest-of-the-connection-string>") .option("tempDir", "abfss://<your-container-name>@<your-storage-account-name>.dfs.core....
importdltdefexist(file_name):# Storage system-dependent function that returns true if file_name exists, false otherwise# This function returns a tuple, where the first value is a DataFrame containing the snapshot# records to process, and the second value is the snapshot version representing the...
()//Can also load data from a Redshift queryvaldf:DataFrame=sqlContext.read .format("com.databricks.spark.redshift") .option("url","jdbc:redshift://redshifthost:5439/database?user=username&password=pass") .option("query","select x, count(*) my_table group by x") .option("tempdir"...