PostgreSQL – Performance Implications of Dropping Unused Surrogate Key Column

performancepostgresqlpostgresql-9.5postgresql-performance

I have a very large (>10m rows) table in a Postgres 9.5.4 database that collects readings from sensors. This table handles many inserts (~2k/minute) but isn't queried too often–only during a cache miss or when rebuilding the cache. Said table is essentially ‘append-only’–there are no updates. However, the queries that I do run are often fairly complex, and I care about optimizing read performance as cache misses can be very slow to a user.

In the business context of relevance, there are sensors that collect energy and power quality data from buildings; there can be multiple sensors for buildings, and a common query is aggregating facility level data. The table schema looks like so:

                                   Table "public.measurement"
    Column     |            Type             |                        Modifiers                         
---------------+-----------------------------+----------------------------------------------------------
 id            | integer                     | not null default nextval('measurement_id_seq'::regclass)
 meter_id      | integer                     | 
 timestamp     | timestamp without time zone | 
 value         | double precision            | 
 _reading_type | smallint                    | 
 facility_id   | integer                     | 
Indexes:
    "measurement_pkey" PRIMARY KEY, btree (id)
    "ix_measurement_timestamp_meter_id__reading_type" btree ("timestamp", meter_id, _reading_type)
    "ix_measurement_timestamp_facility_id__reading_type" btree ("timestamp", facility_id, _reading_type)
Foreign-key constraints:
    "measurement_meter_id_fkey" FOREIGN KEY (meter_id) REFERENCES meter(id)
    "measurement_facility_id_fkey" FOREIGN KEY (facility_id) REFERENCES facility(id)

I am considering dropping the id column, which is a meaningless ‘surrogate key’, as I never, ever query it, but I'm curious what the performance implications would be.

I essentially run two different types of queries on this table:

"Give me all of the measurements between time start and time end of _reading_type 0 for meter_id X", or
"Give me all of the measurements between time start and time end of _reading_type 0 for facility_id X" (I believe the facility_id column denormalizes the table, but saves what was an expensive join).

Questions

What would happen if I do not declare a primary ke?
The combination of (timestamp, meter_id, _reading_type) is guaranteed to be unique, so: what would be the implication of dropping the multicolumn index on these columns and defining a composite primary key?

Best Answer

What would happen if there is no primary key? The combination of timestamp-meter_id-_reading_type is guaranteed to be unique; what would be the implication of dropping the multicolumn index on these columns and making a composite primary key?

You don't need a surrogate key, but you can still use a PRIMARY KEY. It sounds to me like the Primary Key here is

meter_id, reading_id, timestamp

Also you have two of the same keys, drop one of them

"ix_measurement_timestamp_meter_id__reading_type"    btree ("timestamp", meter_id, _reading_type)
"ix_measurement_timestamp_facility_id__reading_type" btree ("timestamp", meter_id, _reading_type)

That's got to be a typo error, but you're just slowing down inserts. At 10 million rows, you may also want to look at partitioning in the upcoming 9.7 or inheritance if you can't upgrade.

This table handles many inserts (1k-2k/second)

You're also not likely doing 2,000 INSERTs a second. That would be 7.2 MILLION an hour. Unless your table gets truncated every 1.5 hours.

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You write:

Each customer can have multiple sites, but only one should be displayed in this list.

Yet, your query retrieves all rows. That would be a point to optimize. But you also do not define which site is to be picked.

Either way, it does not matter much here. Your EXPLAIN shows only 5026 rows for the site scan (5018 for the customer scan). So hardly any customer actually has more than one site. Did you ANALYZE your tables before running EXPLAIN?

From the numbers I see in your EXPLAIN, indexes will give you nothing for this query. Sequential table scans will be the fastest possible way. Half a second is rather slow for 5000 rows, though. Maybe your database needs some general performance tuning?

Maybe the query itself is faster, but "half a second" includes network transfer? EXPLAIN ANALYZE would tell us more.

If this query is your bottleneck, I would suggest you implement a materialized view.

After you provided more information I find that my diagnosis pretty much holds.

The query itself needs 27 ms. Not much of a problem there. "Half a second" was the kind of misunderstanding I had suspected. The slow part is the network transfer (plus ssh encoding / decoding, possibly rendering). You should only retrieve 100 rows, that would solve most of it, even if it means to execute the whole query every time.

If you go the route with a materialized view like I proposed you could add a serial number without gaps to the table plus index on it - by adding a column row_number() OVER (<your sort citeria here>) AS mv_id.

Then you can query:

SELECT *
FROM   materialized_view
WHERE  mv_id >= 2700
AND    mv_id <  2800;

This will perform very fast. LIMIT / OFFSET cannot compete, that needs to compute the whole table before it can sort and pick 100 rows.

pgAdmin timing

When you execute a query from the query tool, the message pane shows something like:

Total query runtime: 62 ms.

And the status line shows the same time. I quote pgAdmin help about that:

The status line will show how long the last query took to complete. If a dataset was returned, not only the elapsed time for server execution is displayed, but also the time to retrieve the data from the server to the Data Output page.

If you want to see the time on the server you need to use SQL EXPLAIN ANALYZE or the built in Shift + F7keyboard shortcut or Query -> Explain analyze. Then, at the bottom of the explain output you get something like this:

Total runtime: 0.269 ms

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Rather than "VARCHAR(40000)" why not use "TEXT"?
HASH index use is discouraged (see docs at http://www.postgresql.org/docs/current/static/indexes-types.html).
Have you run "ANALYZE" on your tables before running the query?
Giant IN lists can be performance killers.

How do the following queries perform?

SELECT e.entityId
FROM entities e
INNER JOIN triples t ON (t.object = e.entityId)
LIMIT 10000;

SELECT e.entityId
FROM entities e
WHERE EXISTS (SELECT 1 FROM triples t WHERE t.object = e.entityId LIMIT 10000);

Best Answer

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