I am new to Tableau, and having performance issues and need some help. I have a hive query result in Azure Blob Storage named as part-00000.
The issue having this performance is I want to execute the custom query in Tableau and generates the graphical reports at Tableau.
So can I do this? How ?
I have 7.0 M Data in Hive table.
you can find custom query in data source connection check linked image
You might want to consider creating an extract instead of a live connection. Additional considerations would include hiding unused fields and using filters at the data source level to limit data as per requirement.
Related
I have about 100 tables to which we replicate data, e.g. from the Oracle database.
I would like to quickly check that the data replicated to the tables in db2 is the same as in the source system.
Does anyone have a way to do this? I can create 100 transformations, but that's monotonous and time consuming. I would prefer to process this in a loop.
I thought I would keep the queries in a table and reach into it for records.
I read the data from Table input (sql_db2, sql_source, table_name) and write do copy rows to result. Next I read single record and I read a single record and put it into a loop.
But here came a problem because I don't know how to dynamically compare the data for the tables. Each table has different columns and here I have a problem.
I don't know if this is also possible?
You can inject metadata (in this case your metadata would be the column and table names) to a lot of steps in Pentaho, you create a transformation to collect the metadata to inject to another transformation that has only the steps and some basic information, but the bulk of the information of the columns affected by the different steps is in the transformation injecting the metadata.
Check Pentaho official documentation about Metadata Injection (MDI) and the sample with a basic example of metadata injection available in your PDI installation.
We curate data in the "Dev" Azure SQL Database and then currently use RedGate's Data Compare tool to push up to 6 higher Azure SQL Databases. I am trying to migrate that manual process to ADFv2 and would like to avoid copy/pasting the 10+ copy data actives for each database (x6) to keep it more maintainable for future changes. The static tables have some customization in the copy data activity but the basic idea follows this post to perform an upsert.
How can the implementation described above be done in Azure Data Factory?
I was imagining something like the following:
Using one parameterized link service that has the server name & database name configurable to generate a dynamic connection to Azure SQL Database.
Creating a pipeline for each table's copy data activity.
Creating a master pipeline to then nest each table's pipeline in.
Using variables loop over the different connections an passing those to the sub-pipelines parameters.
Not sure if that is the most efficient plan or even works yet. Other ideas/suggestions?
we can not tell you if that's the most efficient plan. But I think so. Just make it works.
As you said in the comment:
we can use Dynamic Pipelines - Copy multiple tables in Bulk with
'Lookup' & 'ForEach'. we can perform dynamic copies of your data
table lists in bulk within a single pipeline. Lookup returns either
the lists of data or first row of data. ForEach - #activity('Azure
SQL Table lists').output.value ;
#concat(item().TABLE_SCHEMA,'.',item().TABLE_NAME,'.csv') + This is
efficient and cost optimized since we are using less number of
activities and datasets.
In usually, we also will choose same solution with you: dynamic parameter/pipeline, lookup + foreach active to achieve the scenario. In one word, make the pipeline has a strong logic, simple and efficient.
Added the same info mentioned in the Comment as Answer.
Yup, we can use Dynamic Pipelines - Copy multiple tables in Bulk with 'Lookup' & 'ForEach'.
We can perform dynamic copies of your data table lists in bulk within a single pipeline. Lookup returns either the lists of data or first row of data.
ForEach - #activity('Azure SQL Table lists').output.value ;
#concat(item().TABLE_SCHEMA,'.',item().TABLE_NAME,'.csv')
This is efficient and cost optimized since we are using less number of activities and datasets.
Attached pic as ref-
I need to transform a fairly big database table with aws Glue to csv. However I only the newest table rows from the past 24 hours. There ist a column which specifies the creation date of the row. Is it possible, to just transform these rows, without copying the whole table into the csv file? I am using a python script with Spark.
Thank you very much in advance!
There are some Built-in Transforms in AWS Glue which are used to process your data. This transfers can be called from ETL scripts.
Please refer the below link for the same :
https://docs.aws.amazon.com/glue/latest/dg/built-in-transforms.html
You haven't mentioned the type of database that you are trying connect. Anyway for JDBC connections spark has the option of query, in which you can issue the usual SQL query to get the rows you need.
Does anyone have an experience with large data sets in Data Studio?
I want to use a data that is close to 40 million rows and a dozen columns. I was trying to check it by myself but after connection to BigQuery query a Configuration error occurred.
If you have a dataset stored in BigQuery, Data Studio should have no problem handing it - through BigQuery. Size shouldn't really be a problem.
I've noticed that when Data Studio accesses a BigQuery table, it is limited to 20,000,000 rows.
Specifically, LIMIT 20000000 is applied to the actual query in BQ and there is no way to configure / change that (to the best of my knowledge).
I have a Database with secure Data in some tables(5 tables) when I bring that Database into my Local Environment I need to Mask the Data with Special Characters.
For Example :
Table 1 :
Name Code
Mohan 100
Raju 200
I need to see the data like this
Name Code
M##$n 1#0
R##u 2##
for some of the tables which some sensitive Data
When I get the DB backup with all this data when I'm restoring the Data into my local I need to see the data like this .
Can you please suggest me the best ways or any features in SQL server to mask the Data.
I don't think you can achieve that in a single backup/restore step using only SQL Server 2012. You will either need to write some masking scripts and use those in an ETL workflow or you could consider some data masking products that offer on-the-fly masking (masks the data while copying from source to destination).
If you don't want to write your own masking scripts to do this then you could use the free DataVeil Platform data masking tool and use the Redact mask. Disclaimer: I work for DataVeil.