DecimalType: Represents arbitrary-precision signed decimal numbers. Backed internally byjava.math.BigDecimal. ABigDecimalconsists of an arbitrary precision integer unscaled value and a 32-bit integer scale. String type StringType: Represents character string values. Binary type BinaryType: Represents byte ...
DecimalType: Represents arbitrary-precision signed decimal numbers. Backed internally byjava.math.BigDecimal. ABigDecimalconsists of an arbitrary precision integer unscaled value and a 32-bit integer scale. String type StringType: Represents character string values. Binary type BinaryType: Represents byte ...
, metadata: {org.apache.spark.version=3.0.0, org.apache.spark.sql.parquet.row.metadata={"type":"struct","fields":[{"name":"id1","type":"integer","nullable":false,"metadata":{}},{"name":"id2","type":"long","nullable":false,"metadata":{}},{"name":"id3","type":"decimal(1...
<数值字段/变量/常量1>ASDECIMAL(38,2))/CAST(<数值字段/变量/常量2>ASDECIMAL(3 8,2)));SELECT(CAST(<数值字段/变量/常量1>ASDECIMAL(38,2))/CAST(<数值字段/ 变量/常量2>ASDECIMAL(38,2)));<变量>=spark.sql("""SELECT<数值字段/变量/常量 1>100/<数值字段/变量/常量2>/100""")NULL值替换...
from pyspark.sql.types import * """ __all__ = [ "DataType", "NullType", "StringType", "BinaryType", "BooleanType", "DateType", "TimestampType", "DecimalType", "DoubleType", "FloatType", "ByteType", "IntegerType", "LongType", "ShortType", "ArrayType", "MapType", "StructFi...
StructField("age",IntegerType(),True)])>>> df3=sqlContext.createDataFrame(rdd,schema)>>> df3.collect()[Row(name=u'Alice', age=1)] >>> sqlContext.createDataFrame(df.toPandas()).collect()[Row(name=u'Alice', age=1)]>>> sqlContext.createDataFrame(pandas.DataFrame([[1,2]]))....
ARCHAR(长度)b.UNICODE编码:VARCHAR(长度/2)DDECIMALDECIMAL(精度,标度)DADAT EDATEFORMAT‘格式’IINTEGERINTEGERI8BIGINTBIGINTSELECTCOLUMN_NAMEA S''字段名'',DATA_TYPEAS`数据类型`,CHARACTER_MAXIMUM_LENGTHAS`字符长度`,NU MERIC_PRECISIONAS`数字长度`,NUMERIC_SCALEAS`小数位数`,IS_NULLABLEAS ...
sql.types import DecimalType from decimal import Decimal # Load the text file. df = ( spark.read.format("csv") .option("header", True) .load("data/customer_spend.csv") ) # Convert with a hardcoded custom UDF. money_udf = udf(lambda x: Decimal(x[1:].replace(",", "")), ...
Convert String to Double Convert String to Integer Get the size of a DataFrame Get a DataFrame's number of partitions Get data types of a DataFrame's columns Convert an RDD to Data Frame Print the contents of an RDD Print the contents of a DataFrame Process each row of a DataFrame DataFra...
The only argument you need to pass to.cast()is the kind of value you want to create, in string form. For example, to create integers, you'll pass the argument"integer"and for decimal numbers you'll use"double". You can put this call to.cast()inside a call to.withColumn()to overwr...