一般来说，我建议将数据保存在SAP HANA中，并从那里对其进行操作，但您当然也可以将R Dataframe "保存"到其中。
下面是一个简单的例子：

# load the ODBC driver
library("RODBC")
# open a ODBC "channel" - since I use the SAP HANA secure storage all I have to 
# specify here is the name of the DSN entry. 
ch<-odbcConnect("S12"

# this is just the string for the name of the table the data will be inserted into
table.for.save <- 'AIRQUALITY'
# get the data frame for the AIRQUALITY sample data 
aqdata <- airquality
# that's a data frame
str(aqdata)

# now "save" the data frame to SAP HANA via sqlSave
sqlSave(ch,dat = aqdata, tablename = table.for.save, verbose = TRUE, rownames =  FALSE)

> sqlSave(ch,dat = aqdata, tablename = table.for.save, verbose = TRUE, rownames =  FALSE)

Query: CREATE TABLE "AIRQUALITY"  ("Ozone" INTEGER, "SolarR" INTEGER, "Wind" DOUBLE, "Temp" INTEGER, "Month" INTEGER, "Day" INTEGER)
Query: INSERT INTO "AIRQUALITY" ( "Ozone", "SolarR", "Wind", "Temp", "Month", "Day" ) VALUES ( ?,?,?,?,?,? )
Binding: 'Ozone' DataType 4, ColSize 10
Binding: 'SolarR' DataType 4, ColSize 10
Binding: 'Wind' DataType 8, ColSize 15
Binding: 'Temp' DataType 4, ColSize 10
Binding: 'Month' DataType 4, ColSize 10
Binding: 'Day' DataType 4, ColSize 10
Parameters:
no: 1: Ozone 41/***/no: 2: SolarR 190/***/no: 3: Wind 7.4/***/no: 4: Temp 67/***/no: 5: Month 5/***/no: 6: Day 1/***/
no: 1: Ozone 36/***/no: 2: SolarR 118/***/no: 3: Wind 8/***/no: 4: Temp 72/***/no: 5: Month 5/***/no: 6: Day 2/***/
no: 1: Ozone 12/***/no: 2: SolarR 149/***/no: 3: Wind 12.6/***/no: 4: Temp 74/***/no: 5: Month 5/***/no: 6: Day 3/***/
...

在SAP HANA中，您现在可以从表中SELECT：

select top 10 * from "DEVDUDE"."AIRQUALITY";

Ozone   SolarR  Wind    Temp    Month   Day
41      190     7.4     67      5       1  
36      118     8.0     72      5       2  
12      149     12.6    74      5       3  
18      313     11.5    62      5       4  
?       ?       14.3    56      5       5  
28      ?       14.9    66      5       6  
23      299     8.6     65      5       7  
19      99      13.8    59      5       8  
8       19      20.1    61      5       9  
?       194     8.6     69      5       10

由于这些都是标准的R和ODBC，而不是特定于SAP HANA的，因此我建议阅读这些技术。

这里有一种方法可以做到这一点

tweet_df <- do.call("rbind", lapply(tweets, as.data.frame))

写入csv文件并导入HANA

write.csv(tweet_df,file="twitterList.csv")