New answers tagged

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There is a new approach to solve this problem, it may not be applicable to your case but worths a look I think. Some new databases such as dolt (that have a compatibility with mySQL in term of connector) are able to work like git actually letting you modify data while keeping the original in a previous commit. The modified data is naturally indexed through ...


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because on partitioned tables on Postgres the partition key must belong always to the index This is a misconception, and perhaps accidentally the cause of the problem. The partition key must be part of the primary key or part of a parental unique index, but it does not need to be part of other indexes. So you can create a index on (fk_x_orders_id) on the ...


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You can grant as below instead of altering each table's owner. I faced below error while updating similar table, PG::InsufficientPrivilege: ERROR: must be owner of relation <my table name> Suppose a table was created by a DB user named "createU" and you are trying to perform other operation using another DB user named "updateU" ...


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The manual: Note that you should also create an index with the default operator class if you want queries involving ordinary <, <=, >, or >= comparisons to use an index. Such queries cannot use the xxx_pattern_ops operator classes. (Ordinary equality comparisons can use these operator classes, however.) It is possible to create multiple indexes ...


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If you take the square approximation for the birthday problem with 2128 days in a year (that is the number of different MD5 hashes), and you want to know from how many table rows on the collision probability exceeds 0.000000001, you end up with SELECT sqrt(2 * 2 ^ 128 * 1E-9); sqrt ═════════════════ 824963474247119 (1 row) So even if you had ...


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If category were a regular column and not an expression, PostgreSQL would choose an index-only scan, which would be much faster if the table has been vacuumed recently. But index-only scans are not supported on expression indexes like that, see the documentation: In principle, index-only scans can be used with expression indexes. For example, given an index ...


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I don't know why the results of a biochemical experiment would be enforced to be unique in the first place, but you can use an exclusion constraint that tests for equality. It will automatically resolve hash collisions by doing the character-by-character comparison. alter table foo add constraint foo__bar__un exclude using hash (bar with =); But you should ...


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With the help of the btree_gin extension, you can include an int column into your index, but doing so will not offer you an advantage. The way gin indexes work, it can't be used for ordering. You should write your query first, and worry about optimizing once you have something to optimize.


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I think that's good, because it lowers page contention (vs inserting them all on the last data page all the time), but I'm not sure about that. At insert rates of under 10,000/sec hot page latch contention is not a big issue, and the efficiency and locality of end-of-index inserts is preferable. Change the primary key to be composite on (started, id) so it'...


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A multicolumn expression index should serve your particular query best: CREATE INDEX ON public.core_user (upper(email), last_login DESC); If last_login can be NULL, consider NULLS LAST - in index and query. The rule of thumb is: equality first, range later. See: Multicolumn index and performance Get the last 5 distinct values for each ID


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So could there be edge cases, or should I just cement in my memory to never think about UQ on a column that's already PK, and move on? I'm not sure we can be so unequivocal. It's difficult to say "always" or "never" about anything. There may be an exception case we haven't thought of. Say for example you are in the middle of refactoring ...


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Adding an index is definitely a good idea for this. However, DATEPART(YEAR, datecolumn) = 2012 isnt' sargable so it will still do a scan of the index. If you want it to use the index then you will need to do: WHERE dateColumn >= '1/1/2012' AND dateColumn < '1/1/2013' Please note the placement of the >= and the < signs to get the correct ...


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Answer compiled from comments by: Akina: No reason for to restrict index creation when the statement is syntactically correct. The most common issue - CREATE TABLE t (id SERIAL PRIMARY KEY); which creates both UNIQUE index (due to SERIAL definition) and PRIMARY KEY (due to explicit specifying). So excess UNIQUE key must be removed by an additional statement. ...


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This information can be found in the system tables, sys.spatial_indexes and sys.spatial_index_tessellations. More info for these system tables at https://docs.microsoft.com/en-us/sql/relational-databases/system-catalog-views/spatial-data-catalog-views?view=sql-server-ver15.


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No, there is no functionality like that in sp_BlitzIndex.


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Creating and dropping indexes does not harm the table in the least. Also, with a partial index, you will pay the price for index maintenance only if the row matches the condition. You should consider range partitioning by updated_at. Then queries with that column in the WHERE condition will only scan the necessary partitions. As a side effect, deleting old ...


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The word you're looking for is "SARGable". From Wikipedia: In relational databases, a condition (or predicate) in a query is said to be sargable if the DBMS engine can take advantage of an index to speed up the execution of the query. The term is derived from a contraction of Search ARGument ABLE.


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As with everything related to databases, the answer will be “it depends”. BRIN indexes are efficient if the ordering of the key values follows the organization of blocks in the storage layer. In the simplest case, this could require the physical ordering of the table, which is often the creation order of the rows within it, to match the order of the key(s). ...


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Other than using query hints to force different indexes, or using Query Store to force plans that don't use the index, no. There's no way to "hide" an enabled index from the query optimizer.


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We can't say why, since you posted the SSIS error message. A maintenance plan is an SSIS package. SQL Server returned an error message to SSIS, and SSIS show you something else. You need to hunt down the SQL Server error message. Check the maintenance plan report file, assuming you have such. And the maintenance plan history table as well.


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The two queries are not equivalent. The first query without view runs window functions after applying the WHERE clause. The second query on the view runs window functions before applying the WHERE clause. This can lead to different results. And (obviously) to different query plans. Your second view peniot_json.all_pde_data does not use window functions (or ...


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The second and and third are equivalent. The first is like the third, but adds a (non-unique) index in addition to the unique index. Which is unnecessary and wasteful.


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I only have a little bit of experience with columnstore indexing, but my experience has been awesomely positive so far. I'm assuming when you say the cardinality of the SomeFactTable.NumberA column is ~8 million of the ~9 million records, that you mean they share the same value. If so, then I think a columnstore index would work great for you on it, because ...


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Up to three times than the size of new index: index structure itself WAL records during create index temporary files while sorting index values I have deleted old records in this table It is possible to reclaim space using the pgcompacttable tool. pgcompacttable was designed specifically for compressing tables when there is not enough space for a copy of ...


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Task 1 may be solved by SELECT t1.* FROM test t1 JOIN test t2 USING (b_id, c_id, d_id) WHERE (t1.a_id, t2.a_id) IN ((1,2), (2,1))


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Without much context (if you provide some query examples, then we can better visualize what indexes would be best), creating an index on (a_id, b_id, c_id, d_id) would probably be sufficient, based on what you mentioned. It would cover you for both types of queries, the more common ones that only compare a_id, and would also cover you for comparisons on all ...


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To make this query run fast you will need the data ordered by timestamp. You have a few options If you use a clustered columnstore index you need to FIRST order the data in the table by adding a clustered index on Timestamp and then create the columnstore index using maxdop = 1 and with drop_existing. full syntax https://docs.microsoft.com/en-us/azure/...


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It is not so common that we get questions about why the planner does such a good job! By looking at expected rows values given in the Index Scan Backwards and in the Bitmap Heap Scan (or equivalently the Sort) nodes, we see that for one it expects to find 293 rows, and for the other it expects 7. Yes, this difference does come from the stats. Specifically, ...


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