Import .csv file into cassandra

wish of those help I think your connection is got broken after processing some data. I faced such issue once & solved that by using connection pooling. Can you tell me how you are getting the connection in your java code ?

I hope this helps you . One way to import csv file is by using copy command in cqlsh. I am wondering is there an effective way to import csv file from DevCenter ? , Sorry, there currently is no way to import from CSV using DevCenter.

I wish this helpful for you The commands changed post DSE 4.7. The correct command for doing a thrift import should be:

./dse sqoop thrift-import --connect jdbc:mysql://10.0.0.20/amad \
  --username root \
  --table aminno_mem_email \
  --cassandra-keyspace am_cc \
  --cassandra-table am_cc_cf \
  --cassandra-row-key am_cc_key \
  --cassandra-host 10.0.0.13 \
  --cassandra-create-schema

this one helps. Cassandra doesn't preserve the order of column when creating. You need to specify the column name when importing data.
Try this command :

COPY consumer_complaints (Date_received,Product,Sub_product, Issue, Sub_issue, Consumer_complaint_narrative, Company_public_response, Company, State, ZIP_code, Tags, Consumer_consent_provided, Submitted_via, Date_sent_to_company, Company_response_to_consumer, Timely_response, Consumer_disputed, Complaint_ID) FROM 'c.csv' WITH HEADER = true;

Date_received,Product,Sub_product, Issue, Sub_issue, Consumer_complaint_narrative, Company_public_response, Company, State, ZIP_code, Tags, Consumer_consent_provided, Submitted_via, Date_sent_to_company, Company_response_to_consumer, Timely_response, Consumer_disputed, Complaint_ID
07/26/2013,Mortgage,FHA mortgage,"Loan servicing, payments, escrow account",,,,"CITIBANK, N.A.",NC,28056,,N/A,Web,07/29/2013,Closed with explanation,Yes,No,467750
09/26/2014,Consumer Loan,Vehicle loan,Managing the loan or lease,,,,HSBC NORTH AMERICA HOLDINGS INC.,NY,12572,,N/A,Web,09/26/2014,Closed with explanation,Yes,No,1046323

complaint_id  | company                          | company_public_response | company_response_to_consumer | consumer_complaint_narrative | consumer_consent_provided | consumer_disputed | date_received | date_sent_to_company | issue                                    | product       | state | sub_issue | sub_product  | submitted_via | tags | timely_response | zip_code
--------------+----------------------------------+-------------------------+------------------------------+------------------------------+---------------------------+-------------------+---------------+----------------------+------------------------------------------+---------------+-------+-----------+--------------+---------------+------+-----------------+----------
      1046323 | HSBC NORTH AMERICA HOLDINGS INC. |                    null |      Closed with explanation |                         null |                       N/A |                No |    09/26/2014 |           09/26/2014 |               Managing the loan or lease | Consumer Loan |    NY |      null | Vehicle loan |           Web | null |             Yes |    12572
       467750 |                   CITIBANK, N.A. |                    null |      Closed with explanation |                         null |                       N/A |                No |    07/26/2013 |           07/29/2013 | Loan servicing, payments, escrow account |      Mortgage |    NC |      null | FHA mortgage |           Web | null |             Yes |    28056

With these it helps You're on the right path. The only things you need to add, is a file reader (I saved your data as a .csv file and got it to work), a for-loop to iterate through it, and then an import of the datetime package to convert your dates for the prepared statement.
This worked for me:

with open("/home/aaron/Documents/stackoverflow/test_NYC_taxi.csv", "r") as fares:
    for fare in fares:
        columns=fare.split(",")
        pickup=datetime.datetime.strptime(columns[0],"%Y-%m-%d").date()
        dropoff=datetime.datetime.strptime(columns[1],"%Y-%m-%d").date()
        distance=columns[2]
        fare=columns[3]
        p_long=columns[4]
        p_lat=columns[5]
        d_long=columns[6]
        d_lat=columns[7]

        session.execute(prepared, [pickup,dropoff,distance,fare,p_long,p_lat,d_long,d_lat])

#closing the file
fares.close()

#closing Cassandra connection
session.shutdown()