Using Hibernate's ScrollableResults to slowly read 90 million records

女生的网名这么多〃 提交于 2019-11-26 15:11:47

Using setFirstResult and setMaxResults is your only option that I'm aware of.

Traditionally a scrollable resultset would only transfer rows to the client on an as required basis. Unfortunately the MySQL Connector/J actually fakes it, it executes the entire query and transports it to the client, so the driver actually has the entire result set loaded in RAM and will drip feed it to you (evidenced by your out of memory problems). You had the right idea, it's just shortcomings in the MySQL java driver.

I found no way to get around this, so went with loading large chunks using the regular setFirst/max methods. Sorry to be the bringer of bad news.

Just make sure to use a stateless session so there's no session level cache or dirty tracking etc.

EDIT:

Your UPDATE 2 is the best you're going to get unless you break out of the MySQL J/Connector. Though there's no reason you can't up the limit on the query. Provided you have enough RAM to hold the index this should be a somewhat cheap operation. I'd modify it slightly, and grab a batch at a time, and use the highest id of that batch to grab the next batch.

Note: this will only work if other_conditions use equality (no range conditions allowed) and have the last column of the index as id.

select * 
from person 
where id > <max_id_of_last_batch> and <other_conditions> 
order by id asc  
limit <batch_size>
Sean S.

You should be able to use a ScrollableResults, though it requires a few magic incantations to get working with MySQL. I wrote up my findings in a blog post (http://www.numerati.com/2012/06/26/reading-large-result-sets-with-hibernate-and-mysql/) but I'll summarize here:

"The [JDBC] documentation says:

To enable this functionality, create a Statement instance in the following manner:
stmt = conn.createStatement(java.sql.ResultSet.TYPE_FORWARD_ONLY,
                java.sql.ResultSet.CONCUR_READ_ONLY);
stmt.setFetchSize(Integer.MIN_VALUE);

This can be done using the Query interface (this should work for Criteria as well) in version 3.2+ of the Hibernate API:

Query query = session.createQuery(query);
query.setReadOnly(true);
// MIN_VALUE gives hint to JDBC driver to stream results
query.setFetchSize(Integer.MIN_VALUE);
ScrollableResults results = query.scroll(ScrollMode.FORWARD_ONLY);
// iterate over results
while (results.next()) {
    Object row = results.get();
    // process row then release reference
    // you may need to evict() as well
}
results.close();

This allows you to stream over the result set, however Hibernate will still cache results in the Session, so you’ll need to call session.evict() or session.clear() every so often. If you are only reading data, you might consider using a StatelessSession, though you should read its documentation beforehand."

Haris

Set fetch size in query to an optimal value as given below.

Also, when caching is not required, it may be better to use StatelessSession.

ScrollableResults results = session.createQuery("SELECT person FROM Person person")
        .setReadOnly(true)
        .setFetchSize( 1000 ) // <<--- !!!!
        .setCacheable(false).scroll(ScrollMode.FORWARD_ONLY)
ChechuHa

FetchSize must be Integer.MIN_VALUE, otherwise it won't work.

It must be literally taken from the official reference: https://dev.mysql.com/doc/connector-j/5.1/en/connector-j-reference-implementation-notes.html

einnocent

Actually you could have gotten what you wanted -- low-memory scrollable results with MySQL -- if you had used the answer mentioned here:

Streaming large result sets with MySQL

Note that you will have problems with Hibernate lazy-loading because it will throw an exception on any queries performed before the scroll is finished.

With 90 million records, it sounds like you should be batching your SELECTs. I've done with with Oracle when doing the initial load into a distrbuted cache. Looking at the MySQL documentation, the equivalent seems to be using the LIMIT clause: http://dev.mysql.com/doc/refman/5.0/en/select.html

Here's an example:

SELECT * from Person
LIMIT 200, 100

This would return rows 201 through 300 of the Person table.

You'd need to get the record count from your table first and then divide it by your batch size and work out your looping and LIMIT parameters from there.

The other benefit of this would be parallelism - you can execute multiple threads in parallel on this for faster processing.

Processing 90 million records also doesn't sound like the sweet spot for using Hibernate.

The problem could be, that Hibernate keeps references to all objests in the session until you close the session. That has nothing to do with query caching. Maybe it would help to evict() the objects from the session, after you are done writing the object to the file. If they are no longer references by the session, the garbage collector can free the memory and you won't run out of memory anymore.

smalbequi

I propose more than a sample code, but a query template based on Hibernate to do this workaround for you (pagination, scrolling and clearing Hibernate session).

It can also easily be adapted to use an EntityManager.

I've used the Hibernate scroll functionality successfully before without it reading the entire result set in. Someone said that MySQL does not do true scroll cursors, but it claims to based on the JDBC dmd.supportsResultSetType(ResultSet.TYPE_SCROLL_INSENSITIVE) and searching around it seems like other people have used it. Make sure it's not caching the Person objects in the session - I've used it on SQL queries where there was no entity to cache. You can call evict at the end of the loop to be sure or test with a sql query. Also play around with setFetchSize to optimize the number of trips to the server.

recently i worked over a problem like this, and i wrote a blog about how face that problem. is very like, i hope be helpfull for any one. i use lazy list approach with partial adquisition. i Replaced the limit and offset or the pagination of query to a manual pagination. In my example, the select returns 10 millions of records, i get them and insert them in a "temporal table":

create or replace function load_records ()
returns VOID as $$
BEGIN
drop sequence if exists temp_seq;
create temp sequence temp_seq;
insert into tmp_table
SELECT linea.*
FROM
(
select nextval('temp_seq') as ROWNUM,* from table1 t1
 join table2 t2 on (t2.fieldpk = t1.fieldpk)
 join table3 t3 on (t3.fieldpk = t2.fieldpk)
) linea;
END;
$$ language plpgsql;

after that, i can paginate without count each row but using the sequence assigned:

select * from tmp_table where counterrow >= 9000000 and counterrow <= 9025000

From java perspective, i implemented this pagination through partial adquisition with a lazy list. this is, a list that extends from Abstract list and implements get() method. The get method can use a data access interface to continue get next set of data and release the memory heap:

@Override
public E get(int index) {
  if (bufferParcial.size() <= (index - lastIndexRoulette))
  {
    lastIndexRoulette = index;
    bufferParcial.removeAll(bufferParcial);
    bufferParcial = new ArrayList<E>();
        bufferParcial.addAll(daoInterface.getBufferParcial());
    if (bufferParcial.isEmpty())
    {
        return null;
    }

  }
  return bufferParcial.get(index - lastIndexRoulette);<br>
}

by other hand, the data access interface use query to paginate and implements one method to iterate progressively, each 25000 records to complete it all.

results for this approach can be seen here http://www.arquitecturaysoftware.co/2013/10/laboratorio-1-iterar-millones-de.html

rogerdpack

Another option if you're "running out of RAM" is to just request say, one column instead of the entire object How to use hibernate criteria to return only one element of an object instead the entire object? (saves a lot of CPU process time to boot).

For me it worked properly when setting useCursors=true, otherwise The Scrollable Resultset ignores all the implementations of fetch size, in my case it was 5000 but Scrollable Resultset fetched millions of records at once causing excessive memory usage. underlying DB is MSSQLServer.

jdbc:jtds:sqlserver://localhost:1433/ACS;TDS=8.0;useCursors=true

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