I'm a new PBI user and would like help on the following:
I have 2 tables (Table 1 & 2). Table 1 is a bookings report showing sales orders, part numbers and order value. Table 2 is a margin report showing sales orders, part numbers with additional descriptive text and margin value.
I would like to copy margin values from Table 2 into a new column in Table 1 by looking up by sales order and part number.
Any help would be appreciated!
Tables1
Extract text using the LEFT function
Use the COMBINEVALUES function to create new column in each table. The new column will merge two existing old columns.
Depending if you have unique values in the lookup table, use LOOKUPVALUE function, if not, use this approach: DAX lookup first non blank value in unrelated table
I have two tables, the first table has a list of invoice numbers and the second table has a list of products associated with each invoice. I want to sum the total cost of the products for each invoice and include it in the first table using Excel Power Query.
Table 1
[InvoiceNumbers] [OtherData]
Table 2
[Product] [Amount] [InvoiceNumber]
List.Sum() seems to be the function I need to use, but I cannot filter table 2 by invoice number using this function
Table.SelectRows() can be used to select the second table, and filter it to a specific set of rows, but I cannot seem to filter the rows of Table 2 using a column from Table 1.
I have also looked into Grouping and joining the table, but because of other factors I have left out, this is not going to work.
The full query Im working with looks like this.
List.Sum(Table.SelectRows(Table2, each [InvoiceNumber] = [InvoiceNumber])[Amount])
This just returns the sum of all the rows because [InvoiceNumber] is equal to itself.
How can I reference the Invoice Number of the row in Table 1 to use it as a condition in the Table.SelectRows() function? Or is there a better way to get the data sum the from Table 2?
Table 1 Final
[InvoiceNumber] [OtherData] [SumOfAmounts]
If there is a restriction to group the invoice details table, you could just reference it, and group the reference
1) Reference the table:
2) Group the referenced table:
3) Then merge the reference table and expand the total column
If this helps please remember to mark the answer
I'm loading a large amount of data with SQL Loader.
The target table has a unique, system-generated PK.
When the table is populated by the business application, the key is generated programatically.
The extract file for the bulk upload doesn't have key in the record. Also, the upload is running in multiple threads, because of the extremely large volumes, and in stages - one file a day.
Is there way to populate a column with random key char(14), directly in SQL Loader? In other words, can I have something like that in the Control File:
ID EXPRESSION (random number creation expression),
name char(10),
age number
so from the data file
Joe, 10
Mary, 5
I'll create data:
719287398 Joe 10
645743657 Mary 5
Something like ID EXPRESSION "dbms_random.string('l',14)" can be used.
I've recently started to play around with Cassandra. My understanding is that in a Cassandra table you define 2 keys, which can be either single column or composites:
The Partitioning Key: determines how to distribute data across nodes
The Clustering Key: determines in which order the records of a same partitioning key (i.e. within a same node) are written. This is also the order in which the records will be read.
Data from a table will always be sorted in the same order, which is the order of the clustering key column(s). So a table must be designed for a specific query.
But what if I need to perform 2 different queries on the data from a table. What is the best way to solve this when using Cassandra ?
Example Scenario
Let's say I have a simple table containing posts that users have written :
CREATE TABLE posts (
username varchar,
creation timestamp,
content varchar,
PRIMARY KEY ((username), creation)
);
This table was "designed" to perform the following query, which works very well for me:
SELECT * FROM posts WHERE username='luke' [ORDER BY creation DESC];
Queries
But what if I need to get all posts regardless of the username, in order of time:
Query (1): SELECT * FROM posts ORDER BY creation;
Or get the posts in alphabetical order of the content:
Query (2): SELECT * FROM posts WHERE username='luke' ORDER BY content;
I know that it's not possible given the table I created, but what are the alternatives and best practices to solve this ?
Solution Ideas
Here are a few ideas spawned from my imagination (just to show that at least I tried):
Querying with the IN clause to select posts from many users. This could help in Query (1). When using the IN clause, you can fetch globally sorted results if you disable paging. But using the IN clause quickly leads to bad performance when the number of usernames grows.
Maintaining full copies of the table for each query, each copy using its own PRIMARY KEY adapted to the query it is trying to serve.
Having a main table with a UUID as partitioning key. Then creating smaller copies of the table for each query, which only contain the (key) columns useful for their own sort order, and the UUID for each row of the main table. The smaller tables would serve only as "sorting indexes" to query a list of UUID as result, which can then be fetched using the main table.
I'm new to NoSQL, I would just want to know what is the correct/durable/efficient way of doing this.
The SELECT * FROM posts ORDER BY creation; will results in a full cluster scan because you do not provide any partition key. And the ORDER BY clause in this query won't work anyway.
Your requirement I need to get all posts regardless of the username, in order of time is very hard to achieve in a distributed system, it supposes to:
fetch all user posts and move them to a single node (coordinator)
order them by date
take top N latest posts
Point 1. require a full table scan. Indeed as long as you don't fetch all records, the ordering can not be achieve. Unless you use Cassandra clustering column to order at insertion time. But in this case, it means that all posts are being stored in the same partition and this partition will grow forever ...
Query SELECT * FROM posts WHERE username='luke' ORDER BY content; is possible using a denormalized table or with the new materialized view feature (http://www.doanduyhai.com/blog/?p=1930)
Question 1:
Depending on your use case I bet you could model this with time buckets, depending on the range of times you're interested in.
You can do this by making the primary key a year,year-month, or year-month-day depending on your use case (or finer time intervals)
The basic idea is that you bucket changes for what suites your use case. For example:
If you often need to search these posts over months in the past, then you may want to use the year as the PK.
If you usually need to search the posts over several days in the past, then you may want to use a year-month as the PK.
If you usually need to search the post for yesterday or a couple of days, then you may want to use a year-month-day as your PK.
I'll give a fleshed out example with yyyy-mm-dd as the PK:
The table will now be:
CREATE TABLE posts_by_creation (
creation_year int,
creation_month int,
creation_day int,
creation timeuuid,
username text, -- using text instead of varchar, they're essentially the same
content text,
PRIMARY KEY ((creation_year,creation_month,creation_day), creation)
)
I changed creation to be a timeuuid to guarantee a unique row for each post creation event. If we used just a timestamp you could theoretically overwrite an existing post creation record in here.
Now we can then insert the Partition Key (PK): creation_year, creation_month, creation_day based on the current creation time:
INSERT INTO posts_by_creation (creation_year, creation_month, creation_day, creation, username, content) VALUES (2016, 4, 2, now() , 'fromanator', 'content update1';
INSERT INTO posts_by_creation (creation_year, creation_month, creation_day, creation, username, content) VALUES (2016, 4, 2, now() , 'fromanator', 'content update2';
now() is a CQL function to generate a timeUUID, you would probably want to generate this in the application instead, and parse out the yyyy-mm-dd for the PK and then insert the timeUUID in the clustered column.
For a usage case using this table, let's say you wanted to see all of the changes today, your CQL would look like:
SELECT * FROM posts_by_creation WHERE creation_year = 2016 AND creation_month = 4 AND creation_day = 2;
Or if you wanted to find all of the changes today after 5pm central:
SELECT * FROM posts_by_creation WHERE creation_year = 2016 AND creation_month = 4 AND creation_day = 2 AND creation >= minTimeuuid('2016-04-02 5:00-0600') ;
minTimeuuid() is another cql function, it will create the smallest possible timeUUID for the given time, this will guarantee that you get all of the changes from that time.
Depending on the time spans you may need to query a few different partition keys, but it shouldn't be that hard to implement. Also you would want to change your creation column to a timeuuid for your other table.
Question 2:
You'll have to create another table or use materialized views to support this new query pattern, just like you thought.
Lastly if your not on Cassandra 3.x+ or don't want to use materialized views you can use Atomic batches to ensure data consistency across your several de-normalized tables (that's what it was designed for). So in your case it would be a BATCH statement with 3 inserts of the same data to 3 different tables that support your query patterns.
The solution is to create another tables to support your queries.
For SELECT * FROM posts ORDER BY creation;, you may need some special column for grouping it, maybe by month and year, e.g. PRIMARY KEY((year, month), timestamp) this way the cassandra will have a better performance on read because it doesn't need to scan the whole cluster to get all data, it will also save the data transfer between nodes too.
Same as SELECT * FROM posts WHERE username='luke' ORDER BY content;, you must create another table for this query too. All column may be same as your first table but with the different Primary Key, because you cannot order by the column that is not the clustering column.
I need to query table1 find all orders and created date ( key is order number an date)).
In table 2 ( key is order number an date) Check if the order exists for a a date.
For this i am scanning table 1 and for each record checking if it exists in table 2. Any better way to do this
In this situation in which your key is identical for both tables, it makes sense to have a single table in which you store both data for Table 1 and Table 2. In that way you can do a single scan on your data and know straight away if the data exists for both criteria.
Even more so, if you want to use this data in MapReduce, you would simply scan that single table. If you only want to get the relevant rows, you could define a filter on the Scan. For example, in the case where you will not be populating rows at all in Table 2, you would simply use a ColumnPrefixFilter
If, however, you do need to keep this data separately in 2 tables, you could pre-split the tables with the same region boundaries for both tables - this will be helpful when you do the query that you are aiming for - load all rows in Table 1 when row exists in Table 2. Essentially this would be a map-side join. You could define multiple inputs in your MapReduce job, and since the region borders are the same, the splits will be such that each mapper will have corresponding rows from both tables. You would probably need to implement your own MultipleInput format for that (the MultiTableInputFormat class recently introduced in 0.96 does not seem to do that map side join)