我正在使用pandas chunks功能在csv中阅读。它有效,除了我无法保留标题。有没有办法/选择这样做?这是示例代码:
import pyspark
import pandas as pd
sc = pyspark.SparkContext(appName="myAppName")
spark_rdd = sc.emptyRDD()
# filename: csv file
chunks = pd.read_csv(filename, chunksize=10000)
for chunk in chunks:
spark_rdd += sc.parallelize(chunk.values.tolist())
#print(chunk.head())
#print(spark_rdd.toDF().show())
#break
spark_df = spark_rdd.toDF()
spark_df.show()
答案 0 :(得分:1)
试试这个:
import pyspark
import pandas as pd
sc = pyspark.SparkContext(appName="myAppName")
spark_rdd = sc.emptyRDD()
# Read ten rows to get column names
x = pd.read_csv(filename,nrows=10)
mycolumns = list(x)
# filename: csv file
chunks = pd.read_csv(filename, chunksize=10000)
for chunk in chunks:
spark_rdd += sc.parallelize(chunk.values.tolist())
spark_df = spark_rdd.map(lambda x:tuple(x)).toDF(mycolumns)
spark_df.show()
答案 1 :(得分:0)
我最终使用了数据库'火花CSV
sc = pyspark.SparkContext()
sql = pyspark.SQLContext(sc)
df = sql.read.load(filename,
format='com.databricks.spark.csv',
header='true',
inferSchema='true')