large file from hive to rdbms(oracle)

Recently we have a requirement of dumping a sizable file(4+G) to oracle from s3. The file itself is hive-compatiable. so instead of downloading the file and generate sql for it, we decided to transfer the content using hive jdbc and persist in via jpa/hiberante.


On the hive side, one important thing is to make sure batchsize is set in jdbc resultset.

hiveJdbcTemplate.query(sqlToExecute, rs -> {
            while ({
      you handling


on the relational database side

  1. make sure index is turned off. otherwise it each insertion will trigger the b-tree index to be inserted.
  2. make sure leverage the hibernate batch-size
    hibernate.jdbc.batch_size. I set it to 50 since my table has over 200 columns.For example , if you save() 100 records and your hibernate.jdbc.batch_size is set to 50. During flushing, instead of issue the following SQL 100 times :

    insert into TableA (id , fields) values (1, 'val1');
    insert into TableA (id , fields) values (2, 'val2');
    insert into TableA (id , fields) values (3, 'val3');
    insert into TableA (id , fields) values (100, 'val100');

    Hiberate will group them in batches of 50 , and only issue 2 SQL to the DB, like this:

    insert into TableA (id , fields) values (1, 'val1') , (2, 'val2') ,(3, 'val3') ,(4, 'val4') ,......,(50, 'val50')
    insert into TableA (id , fields) values (51, 'val51') , (52, 'val52') ,(53, 'val53') ,(54, 'val54'),...... ,(100, 'val100')  

    Please note that Hibernate would disable insert batching at the JDBC level transparently if the primary key of the inserting table isGenerationType.Identity.

  3. make sure flush()/clear() for certain size so that memory is not eaten up by the millions of objects built on the fly.
    flush will make sure query be executed and object saved(synced) to DB.
    clear will clear the persistence context so all managed entities are detached. entities that have not been flushed will not be persisted.

My main code is something like:

    public int doImport(int limit)
        String sql = "SELECT * FROM erd.ERD_PRDCT_FIXED_INCM_MNCPL_HS_prc_txt";
        if (limit >= 0)
            sql = sql + " LIMIT " + limit;
        HiveBeanPropertyRowMapper<SrcErdFixedIncmMuniEntity> mapper = new HiveBeanPropertyRowMapper<>(SrcErdFixedIncmMuniEntity.class);
        int batchSize = 5000;
        int[] inc = {0};
        Instant start =;
        List<SrcErdFixedIncmMuniEntity> listToPersist = new ArrayList<>(batchSize);
        hiveJdbcTemplate.query(sql, (rs) -> {
            while (
                listToPersist.add(mapper.mapRow(rs, -1));
                if (inc[0] % batchSize == 0)
                    persistAndClear(inc, listToPersist);
            //left overs(last n items)
                persistAndClear(inc, listToPersist);
            return null;
        Instant end =;
        System.out.println("Data Intake took: " + Duration.between(start, end));
        return inc[0];

    private void persistAndClear(int[] inc, List<SrcErdFixedIncmMuniEntity> listToPersist)
        em.clear();"Saved record milestone: " + inc[0]);


not bad, ~3.5 Millions records get loaded in about an hour.


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