Pandas dataframe in pyspark to hive

first u need to convert pandas dataframe to spark dataframe:

from pyspark.sql import HiveContext
hive_context = HiveContext(sc)
df = hive_context.createDataFrame(pd_df)

then u can create a temptable which is in memory:

df.registerTempTable('tmp')

now,u can use hive ql to save data into hive:

hive_context.sql("""insert overwrite table target partition(p='p') select a,b from tmp'''

note than:the hive_context must be keep to the same one!

I guess you are trying to use pandas df instead of Spark's DF.

Pandas DataFrame has no such method as registerTempTable.

you may try to create Spark DF from pandas DF.

UPDATE:

I've tested it under Cloudera (with installed Anaconda parcel, which includes Pandas module).

Make sure that you have set PYSPARK_PYTHON to your anaconda python installation (or another one containing Pandas module) on all your Spark workers (usually in: spark-conf/spark-env.sh)

Here is result of my test:

>>> import pandas as pd
>>> import numpy as np
>>> df = pd.DataFrame(np.random.randint(0,100,size=(10, 3)), columns=list('ABC'))
>>> sdf = sqlContext.createDataFrame(df)
>>> sdf.show()
+---+---+---+
|  A|  B|  C|
+---+---+---+
| 98| 33| 75|
| 91| 57| 80|
| 20| 87| 85|
| 20| 61| 37|
| 96| 64| 60|
| 79| 45| 82|
| 82| 16| 22|
| 77| 34| 65|
| 74| 18| 17|
| 71| 57| 60|
+---+---+---+

>>> sdf.printSchema()
root
 |-- A: long (nullable = true)
 |-- B: long (nullable = true)
 |-- C: long (nullable = true)