Netezza Batch Insert is very slow even in Batch execute mode - jdbc

Question

I am referring to this documentation. http://www-01.ibm.com/support/docview.wss?uid=swg21981328. As per the article if we use executeBatch method then inserts will be faster (The Netezza JDBC driver may detect a batch insert, and under the covers convert this to an external table load and external table load will be faster). I had to execute millions of insert statements and i am getting only a speed of 500 records per minute per connection max. Is there any better way to load data faster to netezza via jdbc connection? I am using spark and jdbc connection to insert the records.Why external table via loading is not happening even when i am executing in batches. Given below is the spark code i am using,
Dataset<String> insertQueryDataSet.foreachPartition( partition -> {
Connection conn = NetezzaConnector.getSingletonConnection(url, userName, pwd);
conn.setAutoCommit(false);
int commitBatchCount = 0;
int insertBatchCount = 0;
Statement statement = conn.createStatement();
//PreparedStatement preparedStmt = null;
while(partition.hasNext()){
insertBatchCount++;
//preparedStmt = conn.prepareStatement(partition.next());
statement.addBatch(partition.next());
//statement.addBatch(partition.next());
commitBatchCount++;
if(insertBatchCount % 10000 == 0){
LOGGER.info("Before executeBatch.");
int[] execCount = statement.executeBatch();
LOGGER.info("After execCount." + execCount.length);
LOGGER.info("Before commit.");
conn.commit();
LOGGER.info("After commit.");
}
}
//execute remaining statements
statement.executeBatch();
int[] execCount = statement.executeBatch();
LOGGER.info("After execCount." + execCount.length);
conn.commit();
conn.close();
});

Answer 1

I tried this approach(batch insert) but found very slow,
So I put all data in CSV & do external table load for each csv.
InsertReq="Insert into "+ tablename + " select * from external '"+ filepath + "' using (maxerrors 0, delimiter ',' unase 2000 encoding 'internal' remotesource 'jdbc' escapechar '\' )";
Jdbctemplate.execute(InsertReq);
Since I was using java so JDBC as source & note that csv file path is in single quotes .
Hope this helps.
If you find better than this approach, don't forget to post. :)