Mustafa Mustafa - 3 months ago 11x
SQL Question

Splitting large table into 2 dataframes via JDBC connection in RStudio

Through R I connect to a remotely held database. The issue I have is my hardware isn't so great and the dataset contains tens of millions of rows with about 10 columns per table. When I run the below code, at the df step, I get a "Not enough RAM" error from R:

conn <- connect(connectionDetails)
df <- querySql(conn,"SELECT * FROM Table1")

What I thought about doing was splitting the tables into two parts any filter/analyse/combine as needed going forward. I think because I use the conn JDBC conection I have to use SQL syntax to make it work. With SQL, I start with the below code:

df <- querySql(conn,"SELECT TOP 5000000 FROM Table1")

And then where I get stuck is how do I create a second dataframe starting with n - 5000000 rows and ending at the final row, retrieved from Table1.

I'm open to suggestions but I think there are two potential answers to this question. The first is to work within the querySql to get it working. The second is to use an R function other than querySql (no idea what this would look like). I'm limited to R due to work environment.


The SQL statement

SELECT TOP 5000000 * from Table1

is not doing what you think it's doing.

Relational tables are conceptually unordered.

A relation is defined as a set of n-tuples. In both mathematics and the relational database model, a set is an unordered collection of unique, non-duplicated items, although some DBMSs impose an order to their data.

Selecting from a table produces a result-set. Result-sets are also conceptually unordered unless and until you explicitly specify an order for them, which is generally done using an order by clause.

When you use a top (or limit, depending on the DBMS) clause to reduce the number of records to be returned by a query (let's call these the "returned records") below the number of records that could be returned by that query (let's call these the "selected records") and if you have not specified an order by clause, then it is conceptually unpredictable and random which of the selected records will be chosen as the returned records.

Since you have not specified an order by clause in your query, you are effectively getting 5,000,000 unpredictable and random records from your table. Every single time you run the query you might get a different set of 5,000,000 records (conceptually, at least).

Therefore, it doesn't make sense to ask about how to get a second result-set "starting with n - 5000000 and ending at the final row". There is no n, and there is no final row. The choice of returned records was not deterministic, and the DBMS does not remember such choices of past queries. The only conceivable way such information could be incorporated into a subsequent query would be to explicitly include it in the SQL, such as by using a not in condition on an id column and embedding id values from the first query as literals, or doing some kind of negative join, again, involving the embedding of id values as literals. But obviously that's unreasonable.

There are two possible solutions here.

1: order by with limit and offset

Take a look at the PostgreSQL documentation on limit and offset. First, just to reinforce the point about lack of order, take note of the following paragraphs:

When using LIMIT, it is important to use an ORDER BY clause that constrains the result rows into a unique order. Otherwise you will get an unpredictable subset of the query's rows. You might be asking for the tenth through twentieth rows, but tenth through twentieth in what ordering? The ordering is unknown, unless you specified ORDER BY.

The query optimizer takes LIMIT into account when generating query plans, so you are very likely to get different plans (yielding different row orders) depending on what you give for LIMIT and OFFSET. Thus, using different LIMIT/OFFSET values to select different subsets of a query result will give inconsistent results unless you enforce a predictable result ordering with ORDER BY. This is not a bug; it is an inherent consequence of the fact that SQL does not promise to deliver the results of a query in any particular order unless ORDER BY is used to constrain the order.

Now, this solution requires that you specify an order by clause that fully orders the result-set. An order by clause that only partially orders the result-set will not be enough, since it will still leave room for some unpredictability and randomness.

Once you have the order by clause, you can then repeat the query with the same limit value and increasing offset values.

Something like this:

select * from table1 order by id1, id2, ... limit 5000000 offset 0;
select * from table1 order by id1, id2, ... limit 5000000 offset 5000000;
select * from table1 order by id1, id2, ... limit 5000000 offset 10000000;

2: synthesize a numbering column and filter on it

It is possible to add a column to the select clause which will provide a full order for the result-set. By wrapping this SQL in a subquery, you can then filter on the new column and thereby achieve your own pagination of the data. In fact, this solution is potentially slightly more powerful, since you could theoretically select discontinuous subsets of records, although I've never seen anyone actually do that.

To compute the ordering column, you can use the row_number() partition function.

Importantly, you will still have to specify id columns by which to order the partition. This is unavoidable under any conceivable solution; there always must be some deterministic, predictable record order to guide stateless paging through data.

Something like this:

select * from (select *, row_number() over (id1, id2, ...) rn from table1) t1 where rn>0 and rn<=5000000;
select * from (select *, row_number() over (id1, id2, ...) rn from table1) t1 where rn>5000000 and rn<=10000000;
select * from (select *, row_number() over (id1, id2, ...) rn from table1) t1 where rn>10000000 and rn<=15000000;

Obviously, this solution is more complicated and verbose than the previous one. And the previous solution might allow for performance optimizations not possible under the more manual approach of partitioning and filtering. Hence I would recommend the previous solution.

My above discussion focuses on PostgreSQL, but other DBMSs should provide equivalent features. For example, for SQL Server, see Equivalent of LIMIT and OFFSET for SQL Server?, which shows an example of the synthetic numbering solution, and also indicates that (at least as of SQL Server 2012) you can use OFFSET {offset} ROWS and FETCH NEXT {limit} ROWS ONLY to achieve limit/offset functionality.