indexing

问题 I am creating a multi tenant db for an application. I have gone with the TenantID in every table approach and it works very well. I am at the performance tuning stage. My question is should each TenantID in every table be indexed for optimized searching as every query on the db will filter on this column? Look forward to any advice. Thanks 回答1: Although there are many considerations you need to make when indexing, In my experience, the (unique) clustered index works well as tenantId + PK All

问题 In Powershell, how do you overload the indexing of an array operator? Here is what I am doing now: class ThreeArray { $myArray = @(1, 2, 3) [int] getValue ($index) { return $this.myArray[$index] } setValue ($index, $value) { $this.myArray[$index] = $value } } $myThreeArray = New-Object ThreeArray Write-Host $myThreeArray.getValue(1) # 2 $myThreeArray.setValue(2, 5) Write-Host $myThreeArray.getValue(2) # 5 And, I want to do this: $myThreeArray = New-Object ThreeArray Write-Host $myThreeArray[1

问题 I just found that our current database design is a little inefficient according to the SELECT queries we perform the most. IBANs are positional coordinates, according to nation-specific formats. Since we mostly perform JOIN s and WHERE s on a precise substring of IBAN columns in some tables, my question is about assigning an index to the substring(s) of a column Are we forced to add redundant and indexed columns to the table? Ie. add columns NATION_CODE , IBAN_CIN , IT_CIN , IT_ABI , IT_CAB ,

问题 You can create a clustered index on a column other than primary key column if a nonclustered primary key constraint was specified. http://msdn.microsoft.com/en-us/library/ms186342.aspx So the above told me: I can create a clustered index on columns other than primary key. I think it also conveys that a primary key should either be a nonclustered primary key or clustered key. Is it possible a primary key is not indexed? What's more: When you create a UNIQUE constraint, a unique nonclustered

问题 I want to create a procedure that retrieves all indexes on my table and rebuilt i retrieves all indexes with this query: select index_name from user_indexes where table_name='your_table_name' and i rebuilt with this query: alter index <index_name> rebuild; Thx. 回答1: create or replace procedure rebuild_indexes( p_owner in varchar2, p_table_name in varchar2 ) as begin for indexes_to_rebuild in ( select index_name from all_indexes where owner = p_owner and table_name = p_table_name ) loop

问题 I'm trying to make this query to my collection Audios var querySlow = { "palabra": { $regex: "^" + keywords, "$options": "i" }, $or: [{ "_p_pais": { $in: interested_accents } }, { "languageCodeTatoeba": { $in: interested_accents_tatoeba } }] }; // takes 20 seconds This is actually really really slow but if I remove any of the $or , it is very very fast , for example: var queryFast1 = { "palabra": { $regex: "^" + keywords, "$options": "i" }, $or: [{ "_p_pais": { $in: interested_accents } }] };

问题 I'm trying to make this query to my collection Audios var querySlow = { "palabra": { $regex: "^" + keywords, "$options": "i" }, $or: [{ "_p_pais": { $in: interested_accents } }, { "languageCodeTatoeba": { $in: interested_accents_tatoeba } }] }; // takes 20 seconds This is actually really really slow but if I remove any of the $or , it is very very fast , for example: var queryFast1 = { "palabra": { $regex: "^" + keywords, "$options": "i" }, $or: [{ "_p_pais": { $in: interested_accents } }] };

问题 I'm trying to make this query to my collection Audios var querySlow = { "palabra": { $regex: "^" + keywords, "$options": "i" }, $or: [{ "_p_pais": { $in: interested_accents } }, { "languageCodeTatoeba": { $in: interested_accents_tatoeba } }] }; // takes 20 seconds This is actually really really slow but if I remove any of the $or , it is very very fast , for example: var queryFast1 = { "palabra": { $regex: "^" + keywords, "$options": "i" }, $or: [{ "_p_pais": { $in: interested_accents } }] };

问题 Imagine a Pandas dataframe of the following format: id type v1 v2 1 A 6 9 1 B 4 2 2 A 3 7 2 B 3 6 I would like to convert this dataframe into the following format: id A_v1 A_v2 B_v1 B_v2 1 6 9 4 2 2 3 7 3 6 Is there an elegant way of doing this? 回答1: You could use set_index to move the type and id columns into the index, and then unstack to move the type index level into the column index. You don't have to worry about the v values -- where the indexes go dictate the arrangement of the values.

问题 Imagine a Pandas dataframe of the following format: id type v1 v2 1 A 6 9 1 B 4 2 2 A 3 7 2 B 3 6 I would like to convert this dataframe into the following format: id A_v1 A_v2 B_v1 B_v2 1 6 9 4 2 2 3 7 3 6 Is there an elegant way of doing this? 回答1: You could use set_index to move the type and id columns into the index, and then unstack to move the type index level into the column index. You don't have to worry about the v values -- where the indexes go dictate the arrangement of the values.