This is more of a conceptual question. I'm building a relational db, using python and the psycopg2 library, and have a table that has over 44 million rows (and growing) that I want to try and inject sanitized rows from a csv file into the table without injecting duplicate rows; each row has an auto incrementing unique id from it's origin db table.
The current way I'm injecting the data is using the COPY table(columns...) FROM '/path/to/file' command; which is working like a charm. This occurs after we've sanitized all rows in the the csv file to match the datatypes in the rows to the appropriate column's datatypes in the table.
There are a few ideas that I have in mind, and one I've tried, but want to see what the most efficient option is before implementation.
The one I tried ended up being a tremendous burden on the server's cpu and memory; which we have decided not to proceed on. I ended up creating a script that makes a query to the db that searches for the unique id in the table (over 44 million rows).
My other idealistic solutions:
Allow injection of duplicates then create a script to clean up any duplicate rows in the table.
Create a temporary table with the data from the csv. Compare the temp table with the existing table, removing any duplicate values from the temp table, then injecting the temp table into the existing table.
Step 2 might be simplified with this issue. Instead of comparing the two tables we just use the INSERT INTO command along with the ON CONFLICT option.
This one might be more of a stretch of the imagination, and probably pretty unique to our situation. But, since we know that the unique id field will be auto incrementing, we can set a global variable to equal the largest unique id value in the table, then before sanitizing the data we make a query to check if the unique id value is less than the global variable data, and if that is True, we throw out the row from being injected. (No longer an option)
Related
I have roughly 1500 records in an Access database. I have a field ID that acts as the primary key, and as such cannot be manually changed. After looking through the original Excel sheet these records were kept in, I noticed that a few records in Excel were missing from the Access database. After going through all of them, I added the three missing records into Access.
This database stores records in date order, grouped by a manufacturer. Ex. records from Manufacturer1 collected during week 1 of June '16 are all located together, and records from Manufacturer2 collected during week 2 of June '16 are stored directly afterwards. This is important for us because the data in this database often needs to be looked at visually, so keeping things in date order is essential. There is also a macro that export the data to an Excel sheet and formats it to be easier to read, which exports the records in the order in which they are stored (by the ID field). This is a problem because the three missing records are from years past - now they are in the middle of records from 2018. The IDs they were assigned upon entry keeps them in that location.
Is there a way to reliably insert these records into the database in the location at which they should be? Such as shifting the values of other records ID fields down by 3 to allow room for the missing records? I know I can probably manually have those three records move to the desired location in the macro that exports to Excel, but I'd rather have a less hacky solution that could work if a similar problem happens again.
The order of data in a database is of no interest to the database - it's the relation between data that matters.
To always view your data in the order you want use the ORDER BY clause in an SQL statement. Generally you can add data to the underlying table directly through the query - unless you've got many-to-one type queries where your update would need to affect more than one record.
SELECT FieldName1, FieldName2, . . . .
FROM MyDataTable
ORDER BY Manufacturer, Date
Edit: Even here you'll be adding new records to the bottom of the dataset, but refreshing the query will move the records to the correct order.
I hava created a cassandra table with 20 million records. Now I want to delete the expired data decided by one none primary key column. But it doesn't support the operation on the column. So I try to retrieve the table and get the data line by line to delete the data.Unfortunately,it is too huge to retrieve. Otherwise,I couldn't delete the whole table, how could I achieve my goal?
Your question is actually, how to get the data from the table in bulks (also called pagination).
You can do that by selecting different slices from your primary key: For example, if your primary key is some sort of ID, select a range of IDs each time, process the results and do whatever you want to do with them, then get the next range, and so on.
Another way, which depends on the driver you're working with, will be to use fetch_size. You can see a Python example here and a Java example here.
As known, in relational databases, when adding a new column, data must be reallocated (ALTER TABLE without locking the table?) to maintain a single row contiguous on disk.
I would like to understand how this is achieved on wide-columns storages such as Cassandra, which are sparses and can handle lots of dynamic columns insertions (http://www.datastax.com/dev/blog/thrift-to-cql3 (Dynamic Column family))
Thanks!
In Cassandra adding a Column is adding a bit like adding row in relational database. You can even delete a column for a specific row:
delete first_name from user where user_id='abcd';
In CQL, alter table doesn't modify all rows, in short it just modifies the schema dictionary which describe tables (look at tables prefixed schema_ in the system keyspace). This changes only CQL parsing (the new column is now recognized) and interpretation (select * from user meaning is changed).
When you drop a column, data doesn't appear anymore in query results yet it is still present in SSTables. The data will be removed (and space freed) during a future compaction (like tombstones).
I am building a web site that has a wish list. I want to store the wish list(s) in azure table storage, but also want the user to be able to sort their wish list, when viewing it, a number of different ways - date added, date added reversed, item name etc. I also want to implement paging which I believe I can implement by making use of the continuation token.
As I understand it, "order by" isn't implemented and the order that results are returned from table storage is based on the partition key and row key. Therefore if I want to implement the paging and sorting that I describe, is the best way to implement this by storing the wish list multiple times with different partition key / row key?
In this simple case, it is likely that the wish list won't be that large and I could in fact restrict the maximum number of items that can appear in the list, then get rid of paging and sort in memory. However, I have more complex cases that I also need to implement paging and sorting for.
On today’ s hardware having 1000’s of rows to hold, in a list, in memory and sort is easily supportable. What the real issue is, how possible is it for you to access the rows in table storage using the Keys and not having to do a table scan. Duplicating rows across multiple tables could get quite cumbersome to maintain.
An alternate solution, would be to temporarily stage your rows into SQL Azure and apply an order by there. This may be effective if your result set is too large to work in memory. For best results the temporary table would need to have the necessary indexes.
Azure Storage keeps entities in lexicographical order, indexed by Partition Key as primary index and Row Key as secondary index. In general for your scenario it sounds like UserId would be a good fit for a partition key, so you have the Row Key to optimize for per each query.
If you want the user to see the wish lists latest on top, then you can use the log tail pattern where your row key will be the inverted Date Time Ticks of the DateTime when the wish list was entered by the user.
https://learn.microsoft.com/azure/storage/tables/table-storage-design-patterns#log-tail-pattern
If you want user to see their wish lists ordered by the item name you could have your item name as your row key, and so the entities will naturally sorted by azure.
When you are writing the data you may want to denormalize the data and do multiple writes with these different row key schemas. Since you will have the same partition key as user id, you can at that stage do a batch insert operation and not worry about consistency since azure table batch operations are atomic.
To differentiate the different rowkey schemas, you may want to prepend each with a const string value. Like your inverted ticks row key value for instance woul dbe something like "InvertedTicks_[InvertedDateTimeTicksOfTheWishList]" and your item names row key value would be "ItemName_[ItemNameOfTheWishList]"
Why not do all of this in .net using a List.
For this type of application I would have thought SQL Azure would have been more appropriate.
Something like this worked just fine for me:
List<TableEntityType> rawData =
(from c in ctx.CreateQuery<TableEntityType>("insysdata")
where ((c.PartitionKey == "PartitionKey") && (c.Field == fieldvalue))
select c).AsTableServiceQuery().ToList();
List<TableEntityType> sortedData = rawData.OrderBy(c => c.DateTime).ToList();
Rookie question I know.
I have a table with about 10 fields, one of the fields is a category field. I need this field to exist because of the multiple types of categories. However, one category in this field is wrong and is duplicating results.
So can I delete all records in the table that have "Type320" in the CatDescription field, and how? I want to keep eveerything else as it is in this table; just need to get rid of the records that have that that in that one field
Thanks very much!
EDIT: Thanks for the answer, I did not know how to do this so this is very helpful
However, this is more complicated than I thought. The raw data that I am supplied carries these duplicate records (only duplicate in certain circumstances but they are easy to isolate). This raw data is given to me on a monthly basis in several spreadsheet forms.
It all relates to these ID numbers, and has like 10 fields (xls columns). As I said before one of these is the Category Description field (sorry, this is not a lookup) In certain places this records automatically duplicates itself on output because in the database this comes from, it has to have this sub category for one particular "type"
So....every time there is a duplication, every single bit of information in all fields are exactly the same, with the exception of this CatDescription (one is Type320, and the duplicated record type is "Type321"). However, there are some instances where Type321 is valid on it's own (in which case there is no matching data row with a Type320 catdescription). By matching I mean all data in all fields of a particular record.
A very clear absolute of this is if all fields (data within) of a record with Type320 CatDescription, matches all fields (data within) a record with Type321 CatDescription, then I can delete that record containing Type321 CatDescription. This is true because this is the only situation where this duplication occurs, normally not all of this should match.
This allows all unique records with Type320 and Type321 data (that does not match exactly) to stay; just a it should. This makes sense to me (and hopefully you too :/) but can it be done, and how?
thanks because this is way over my head. I would rather know how to do it in access, but an xls solution is equally as appreciate. heck i would do it in ppt if it would get the job done! :)
I would try with one of these two querys:
DELETE FROM table WHERE CatDescription LIKE '%Type320%';
DELETE FROM table WHERE CatDescription LIKE '*Type320*';
That because the Access database engine could be using * (ANSI-89 Query Mode e.g. DAO) instead of % (ANSI-92 Query Mode e.g. OLE DB/ADO) for the wildcards.
Alternatively, this regardless of ANSI Query Mode:
DELETE FROM table WHERE CatDescription ALIKE '%Type320%';
Note the Access database engine's ALIKE keyword is not officially supported.
Does the CatDescription field look to another table? Is it a a query of those tables that creates what you call duplicate results?
If so, be careful about blaming the table that has CatDescription. Check the look-up table to see if Type320 is found there in duplicate.
If you don't have the problem isolated correctly, then you're likely to delete good records while not fixing the problem.