Say we have a denormalized table where the row size is quite big.
When oracle is performing a sort by (in memory):
Is it loading in memory the whole row just to check a small column to order? or is it just loading in memory the ID and the column to sort?
Is the behavior when doing a sort in disk different?
It only sorts the required data, which includes the order-by columns and the data being projected.
If you select ten columns from a fifty column table, and sort by two columns not selected, then 12 columns are included in the sort area requirements.
Related
I'm trying to figure out how to write a parquet file where the columns do not contain the same number of rows per Row Group. For example, my first column might be a value sampled at 10Hz, while my second column may be a value sampled at only 5Hz. I'd rather not repeat values in the slower column since this can lead to computational errors. However, I cannot write columns of two different sizes to the same Row Group, so how can I accomplish this?
I'm attempting to do this with ParquetSharp.
It is not possible for the columns in a parquet file to have different row counts.
It is not explicit in the documentation but if you look on https://parquet.apache.org/documentation/latest/#metadata, you will see that a RowGroup has a num_rows and several ColumnChunks that do not themselves have individual row numbers.
I have a boolean table with ~100000 rows and 3000 columns. I know that many of these columns are redundant because they are the result of OR between some other columns in the table (even maybe up to 200 other columns). The structure is also nested - some columns may be constructed from ORing other columns and then themselves be involved in creating a new column.
My goal is to reduce this table into "base columns" and a list of OR rules which allow me to reconstruct the original data.
Is there any way to do this in a reasonable amount of run-time?
My users table doesn't have many rows... yet. 😏
Might the query plan of the same query change as the table grows?
I.e., to see how my application will scale, should I seed my users table with BILLIONS 🤑 of rows before using EXPLAIN?
Estimated row counts are probably the most important factor that influence which query plan is chosen.
Two examples that support this:
If you use a WHERE condition on an indexed column of a table, three things can happen:
If the table is very small or a high percentage of the rows match the condition, a sequential scan will be used to read the whole table and filter out the rows that match the condition.
If the table is large and a low percentage of the rows match the condition, an index scan will be used.
If the table is large and a medium percentage of rows match the condition, a bitmap index scan will be used.
If you join two tables, the estimated row counts on the tables will determine if a nested loop join is chosen or not.
I found some bottleneck of my query which select data from only single table then require time and i used non unique key index on two column and with column used in where clause.
select name ,isComplete from Student where year='2015' and isComplete='F'
Now i found some concept from internet like skewed column so what is it?
have an idea then plz help me?
and how to resolve problem of skewed column?
and how skewed column affect performance of the Query?
Skewed columns are columns in which the data is not evenly distributed among the rows.
For example, suppose:
You have a table order_lines with 100,000,000 rows
The table has a column named customer_id
You have 1,000,000 distinct customers
Some (very large) customers can have hundreds of thousands or millions of order lines.
In the above example, the data in order_lines.customer_id is skewed. On average, you'd expect each distinct customer_id to have 100 order lines (100 million rows divided by 1 million distinct customers). But some large customers have many, many more than 100 order lines.
This hurts performance because Oracle bases its execution plan on statistics. So, statistically speaking, Oracle thinks it can access order_lines based on a non-unique index on customer_id and get only 100 records back, which it might then join to another table or whatever using a NESTED LOOP operation.
But, then when it actually gets 1,000,000 order lines for a particular customer, the index access and nested loop join are hideously slow. It would have been far better for Oracle to do a full table scan and hash join to the other table.
So, when there is skewed data, the optimal access plan depends on which particular customer you are selecting!
Oracle lets you avoid this problem by optionally gathering "histograms" on columns, so Oracle knows which values have lots of rows and which have only a few. That gives the Oracle optimizer the information it needs to generate the best plan in most cases.
Full table scan and Index Scan both are depend on the Skewed column.
and Skewed column is nothing but your spread like gender column contain 60 male and 40 female.
I'm currently doing some data loading for a kind of warehouse solution. I get an data export from the production each night, which then must be loaded. There are no other updates on the warehouse tables. To only load new items for a certain table I'm currently doing the following steps:
get the current max value y for a specific column (id for journal tables and time for event tables)
load the data via a query like where x > y
To avoid performance issues (I load around 1 million rows per day) I removed most indices from the tables (there are only needed for production, not in the warehouse). But that way the retrieval of the max value takes some time...so my question is:
What is the best way to get the current max value for a column without an index on that column? I just read about using the stats but I don't know how to handle columns with 'timestamp with timezone'. Disabling the index before load, and recreate it afterwards takes much too long...
The minimum and maximum values that are computed as part of column-level statistics are estimates. The optimizer only needs them to be reasonably close, not completely accurate. I certainly wouldn't trust them as part of a load process.
Loading a million rows per day isn't terribly much. Do you have an extremely small load window? I'm a bit hard-pressed to believe that you can't afford the cost of indexing the row(s) you need to do a min/ max index scan.
If you want to avoid indexes, however, you probably want to store the last max value in a separate table that you maintain as part of the load process. After you load rows 1-1000 in table A, you'd update the row in this summary table for table A to indicate that the last row you've processed is row 1000. The next time in, you would read the value from the summary table and start at 1001.
If there is no index on the column, the only way for the DBMS to find the maximum value in the column is a complete table scan, which takes a long time for large tables.
I suppose a DBMS could try to keep track of the minimum and maximum values in the column (storing the values in the system catalog) as it does inserts, updates and deletes - but deletes are why no DBMS I know of tries to keep statistics up to date with per-row operations. If you delete the maximum value, finding the new maximum requires a table scan if the column is not indexed (and if it is indexed, the index makes it trivial to find the maximum value, so the information does not have to be stored in the system catalog). This is why they're called 'statistics'; they're an approximation to the values that apply. But when you request 'SELECT MAX(somecol) FROM sometable', you aren't asking for statistical maximum; you're asking for the actual current maximum.
Have the process that creates the extract file also extract a single row file with the min/max you want. I assume that piece is scripted on some cron or scheduler, so shouldn't be too much to ask to add min/max calcs to that script ;)
If not, just do a full scan. Million rows isn't much really, esp in a data warehouse environment.
This code was written with oracle, but should be compatible with most SQL versions:
This gets the key of the max(high_val) in the table according to the range.
select high_val, my_key
from (select high_val, my_key
from mytable
where something = 'avalue'
order by high_val desc)
where rownum <= 1
What this says is: Sort mytable by high_val descending for values where something = 'avalue'. Only grab the top row, which will provide you with the max(high_val) in the selected range and the my_key to that table.