Oracle order by query very slow - oracle10g

I am facing a problem when doing order by on a table.
My select query is working fine, but when i do order by (even on the primary key) it just goes on and on with no results. Finally i need to kill the session. The table has20K records.
Any suggestion for the this?
Query is as:
SELECT * FROM Users ORDER BY ID;
I do not about know about the query plan as i am new to oracle

For the unordered query, Is SQL Developer retrieving and displaying 20K rows, or just the fisrt 50? Your comparison might not be fair.
What is the size of those 20K rows: select bytes/1024/1024 MB from user_segments where segment_name = 'USERS'; I've seen many cases where a few megabytes of data use many gigabytes of storage. Maybe the data was very large before and somebody just deleted it (this doesn't remove the space). Or maybe somebody inserted those rows 1 at a time with an APPEND hint, and each row is taking an entire block.
Your query might be waiting for more temp tablespace for sorting, look at DBA_RESUMABLE.

Related

How to select unique records from table with big number of records

I use postgresql and I have a database table with more than 5 million records. The structure of the table is as follows:
A lot of records is inserted every day. There are many records with the same reference.
I want to select all records but I do not want duplicates, the records with the same reference.
I tried with query as follows:
SELECT DISTINCT ON (reference) reference_url, reference FROM daily_run_vehicle WHERE handled = False and retries < 5 ORDER BY reference DESC;
It executed, it gives me correct result, but it takes to long to execute.
Is there any better way to do this?
Create Sort keys on columns which yo used in where condition
after large data movement into the table, we need to do "vacuum" command it will refresh all the keys and after that Analyze the table with "Analyze" command. it will help to rebuild the stats of the table.

How can I speed up a Postgres query, in which I want to query all entries within a date range

So I'm doing this query
select * from table where time>'2019-01-28 04:13:36.790000' and time<'2019-01-28 04:13:46.790000';
It used to be very fast, but as the table grew it's now taking several minutes to complete. I'm not exactly sure how many entries are in the table. I'm guessing tens of millions. I just want to be able to query entries in a given time interval. Is there anything I can do to the table to make this quicker.
It's hard to say for sure without more context, but if you don't already have an index on time, consider adding one.
CREATE INDEX idx_table_time ON table (time ASC)

Query on large, indexed table times out

I am relatively new to using Postgres, but am wondering what could be the workaround here.
I have a table with about 20 columns and 250 million rows, and an index created for the timestamp column time (but no partitions).
Queries sent to the table have been failing (although using the view first/last 100 rows function in PgAdmin works), running endlessly. Even simple select * queries.
For example, if I want to LIMIT a selection of the data to 10
SELECT * from mytable
WHERE time::timestamp < '2019-01-01'
LIMIT 10;
Such a query hangs - what can be done to optimize queries in a table this large? When the table was of a smaller size (~ 100 million rows), queries would always complete. What should one do in this case?
If time is of data type timestamp or the index is created on (time::timestamp), the query should be fast as lightning.
Please show the CREATE TABLE and the CREATE INDEX statement, and the EXPLAIN output for the query for more details.
"Query that doesn't complete" usually means that it does disk swaps. Especially when you mention the fact that with 100M rows it manages to complete. That's because index for 100M rows still fits in your memory. But index twice this size doesn't.
Limit won't help you here, as database probably decides to read the index first, and that's what kills it.
You could try and increase available memory, but partitioning would actually be the best solution here.
Partitioning means smaller tables. Smaller tables means smaller indexes. Smaller indexes have better chances to fit into your memory.

Select * from table_name is running slow

The table contains around 700 000 data. Is there any way to make the query run faster?
This table is stored on a server.
I have tried to run the query by taking the specific columns.
If select * from table_name is unusually slow, check for these things:
Network speed. How large is the data and how fast is your network? For large queries you may want to think about your data in bytes instead of rows. Run select bytes/1024/1024/1024 gb from dba_segments where segment_name = 'TABLE_NAME'; and compare that with your network speed.
Row fetch size. If the application or IDE is fetching one-row-at-a-time, each row has a large overhead with network lag. You may need to increase that setting.
Empty segment. In a few weird cases the table's segment size can increase and never shrink. For example, if the table used to have billions of rows, and they were deleted but not truncated, the space would not be released. Then a select * from table_name may need to read a lot of empty extents to get to the real data. If the GB size from the above query seems too large, run alter table table_name move; to rebuild the table and possible save space.
Recursive query. A query that simple almost couldn't have a bad execution plan. It's possible, but rate, for a recursive query has a bad execution plan. While the query is running, look at select * from gv$sql where users_executing > 0;. There might be a data dictionary query that's really slow and needs to be tuned.

Caching various statistics in a special one row table?

Expecting hundreds of millions of rows and write-heavy applciation.
We need return SELECT COUNT(*) FROM orders and SELECT SUM(amount) FROM orders quite frequently and both of them are too slow to be ran on every request.
We are thinking about adding a special table called stats with just a single row. It has total_orders and total_amount, which we would increase every time we add a new order. Is this kind of SQL "cache" table a practical solution? What does it mean in terms of write performance?
Another option is to use Memcached or Redis, but they can get out of sync and are not persistent. Any other ideas?