I am building a pipeline that connects to an on-prem Oracle DB using the Database Plugin, queries two tables (table_a, table_b), and joins those tables using Joiner Plugin, before uploading to a BigQuery table.
The problem I have now is that the Foreign Keys to join table_a and table_b have different data types when I use Get Schema in the Database Plugin. In Joiner, I am joining the tables on table_a.customer_id = table_b.customer_id.
The dtype of table_a.customer_id is LONG but table_b.customer_id is DOUBLE. In the source Oracle DB, both columns are actually integers. For some reason, though, using Get Schema thinks they are LONG and DOUBLE.
I am obviously getting an error in Joiner trying to join on a foreign keys with different data types.
Is there a way to cast/convert the columns from the tables to match so that I can use Joiner?
I've seen some examples using Wrangler Transform to parse dates, but I don't see anything to convert to any other data types. I couldn't find any directive examples either: https://github.com/data-integrations/wrangler.
You can transform your data before joining them by using any of the transform plugins that Cloud Data Fusion offers. As #muscat mentioned, you can use Wrangler transform and utilize the Set type directives, or you can use the Projection transform and configure the Convert field.
Related
I need to store/map one or more data flow parameters to my Sink (Azure SQL Table).
I can fetch other data from a REST Api and is able to map these to my Sink columns (see below). I also need to generate some UUID's as key fields and add these to the same table.
I would like my EmployeeId column to contain my Data Flow Input parameter, e.g. named param_test. In addition to this I need to insert UUID's to other columns which are not part of my REST input fields.
How to I acccomplish that?
You need to use a derived column transformation, and there edit the expression to include the parameters.
derived column transformation
expression builder
Adding to #Chen Hirsh, use the same derived column to get uuid values to the columns after REST API Source.
They will come into sink mapping:
Output:
I have an azure pipeline that moves data from one point to another in parquet files. I need to join some data from a Postgresql database that is in an AWS tenancy by a unique ID. I am using a dataflow to create the unique ID I need from two separate columns using a concatenate. I am trying to create where clause e.g.
select * from tablename where unique_id in ('id1','id2',id3'...)
I can do a lookup query to the database, but I can't figure out how to create the list of IDs in a parameter that I can use in the select statement out of the dataflow output. I tried using a set variable and was going to put that into a for-each, but the set variable doesn't like the output of the dataflow (object instead of array). "The variable 'xxx' of type 'Array' cannot be initialized or updated with value of type 'Object'. The variable 'xxx' only supports values of types 'Array'." I've used a flatten to try to transform to array, but I think the sync operation is putting it back into JSON?
What a workable approach to getting the IDs into a string that I can put into a lookup query?
Some notes:
The parquet file has a small number of unique IDs compared to the total unique IDs in the database.
If this were an azure postgresql I could just use a join in the dataflow to do the join, but the generic postgresql driver isn't available in dataflows. I can't copy the entire database over to Azure just to do the join and I need the dataflow in Azure for non-technical reasons.
Edit:
For clarity sake, I am trying to replace local python code that does the following:
query = "select * from mytable where id_number in "
df = pd.read_parquet("input_file.parquet")
df['id_number'] = df.country_code + df.id
df_other_data = pd.read_sql(conn, query + str(tuple(df.id_number))
I'd like to replace this locally executing code with ADF. In the ADF process, I have to replace the transformation of the IDs which seems easy enough if a couple of different ways. Once I have the IDs in the proper format in a column in a dataset, I can't figure out how to query a database that isn't supported by Data Flow and restrict it to only the IDs I need so I don't bring down the entire database.
Due to variables of ADF only can store simple type. So we can define an Array type paramter in ADF and set default value. Paramters of ADF support any type of elements including complex JSON structure.
For example:
Define a json array:
[{"name": "Steve","id": "001","tt_1": 0,"tt_2": 4,"tt3_": 1},{"name": "Tom","id": "002","tt_1": 10,"tt_2": 8,"tt3_": 1}]
Define an Array type paramter and set its default value:
So we will not get any error.
I have a basic REST service backed by a PostgreSQL database with a table with various columns, one of which is a JSONB column that contains arbitrary data. Clients can store data filling in the fixed columns and provide any JSON as opaque data that is stored in the JSONB column.
I want to allow the client to query the database with constraints on both the fixed columns and the JSONB. It is easy to translate some query parameters like ?field=value and convert that into a parameterized SQL query for the fixed columns, but I want to add an arbitrary JSONB query to the SQL as well.
This JSONB query string could contain SQL injection, how can I prevent this? I think that because the structure of the JSONB data is arbitrary I can't use a parameterized query for this purpose. All the documentation I can find suggests I use parameterized queries, and I can't find any useful information on how to actually sanitize the query string itself, which seems like my only option.
For example a similar question is:
How to prevent SQL Injection in PostgreSQL JSON/JSONB field?
But I can't apply the same solution as I don't know the structure of the JSONB or the query, I can't assume the client wants to query a particular path using a particular operator, the entire JSONB query needs to be freely provided by the client.
I'm using golang, in case there are any existing libraries or code fragments that I can use.
edit: some example queries on the JSONB that the client might do:
(content->>'company') is NULL
(content->>'income')::numeric>80000
content->'company'->>'name'='EA' AND (content->>'income')::numeric>80000
content->'assets'#>'[{"kind":"car"}]'
(content->>'DOB')::TIMESTAMP<'2000-01-30T10:12:18.120Z'::TIMESTAMP
EXISTS (SELECT FROM jsonb_array_elements(content->'assets') asset WHERE (asset->>'value')::numeric > 100000)
Note that these don't cover all possible types of queries. Ideally I want any query that PostgreSQL supports on the JSONB data to be allowed. I just want to check the query to ensure it doesn't contain sql injection. For example, a simplistic and probably inadequate solution would be to not allow any ";" in the query string.
You could allow the users to specify a path within the JSON document, and then parameterize that path within a call to a function like json_extract_path_text. That is, the WHERE clause would look like:
WHERE json_extract_path_text(data, $1) = $2
The path argument is just a string, easily parameterized, which describes the keys to traverse down to the given value, e.g. 'foo.bars[0].name'. The right-hand side of the clause would be parameterized along the same rules as you're using for fixed column filtering.
I want to use my column data in other columns for arithmetic operations. I am fetching data using join. Is there a way to access this data by index. However, table is same. I am using postgresql. Hopes for suggestion
I am currently experimenting with Tableau Extract API to generate some TDE from the tables I have in a PostgreSQL database. I was able to write a code to generate the TDE from single table, but I would like to do this for multiple joined tables. To be more specific, if I have two tables that are inner joined by some field, how would I generate the TDE for this?
I can see that if I am working with small number of tables, I could use a SQL query with JOIN clauses to create a one gigantic table, and generate the TDE from that table.
>> SELECT * FROM table_1 INNER JOIN table_2
INTO new_table_1
ON table_1.id_1 = table_2.id_2;
>> SELECT * FROM new_table_1 INNER JOIN TABLE_3
INTO new_table_2
ON new_table_1.id_1 = table_3.id_3
and then generate the TDE from new_table_2.
However, I have some tables that have over 40 different fields, so this could get messy.
Is this even a possibility with current version of the API?
You can read from as many tables or other sources as you want. Or use complex query with lots of joins, or create a view and read from that. Usually, creating a view is helpful when you have a complex query joining many tables.
The data extract API is totally agnostic about how or where you get the data to feed it -- the whole point is to allow you to grab data from unusual sources that don't have pre-built drivers for Tableau.
Since Tableau has a Postgres driver and can read from it directly, you don't need to write a program with the data extract API at all. You can define your extract with Tableau Desktop. If you need to schedule automated refreshes of the extract, you can use Tableau Server or its tabcmd command.
Many thanks for your replies. I am aware that I could use Tableau Desktop to define my extract. In fact, I have done this many times before. I am just trying to create the extracts using the API, because I need to create some calculated fields, which is near impossible to create using the Tableau Desktop.
At this point, I am hesitant to use JOINs in the SQL query because the resulting table would look too complicated to comprehend (some of these tables also have same field names).
When you say that I could read from multiple tables or sources, does that mean with the Tableau Extract API? At this point, I cannot find anywhere in this API that accommodates multiple sources. For example, I know that when I use multiple tables in the Tableau Desktop, there are icons on the left hand side that tells me that the extract is composed of multiple tables. This just doesn't seem to be happening with the API, which leaves me stranded. Anyways, thank you again for your replies.
Going back to the topic, this is something that I tried few days ago on my python code
try:
tdefile= tde.Extract("extract.tde")
except:
os.remove("extract.tde")
tdefile = tde.Extract("extract.tde")
tableDef = tde.TableDefinition()
# Read each column in table and set the column data types using tableDef.addColumn
# Some code goes here...
for eachTable in tableNames:
tableAdd = tdeFile.addTable(eachTable, tableDef)
# Use SQL query to retrieve bunch_of_rows from eachTable
for some_row in bunch_of_rows:
# Read each row in table, and set the values in each column position of each row
# Some code goes here...
tableAdd.insert(some_row)
some_row.close()
tdefile.close()
When I execute this code, I get the error that eachTable has to be called "Extract".
Of course, this code has its flaws, as there is no where in this code that tells how each table are being joined.
So I am little thrown off here, because it doesn't seem like I can use multiple tables unless I use JOINs to generate one table that contains everything.