GCP now offers a lovely feature to replicate postgres tables directly into Bigquery.
I have managed to get this functionality setup pretty simply following the docs, however all of the columns of ENUM data type are not being converted and pushed into Bigquery.
Is there a solution for this?
https://cloud.google.com/datastream-for-bigquery
Related
I’m trying to create a continuous migration job from Aws S3 to Redshift using Aws Glue.
I wish to load object data types to Redshift as super type directly in Aws Glue.
However during the function glueContext.write_dynamic_frame.from_jdbc_conf, If the data contains an object data type, I get an error msg "CSV data source does not support struct data type" and I am aware of the cause of the error.
An option would be to use pyspark.sql.functions.to_json to the object data and later use json_extract_path_text() when querying the objects in Redshift.
But I hope there is an approach in AWS glue, that supports a direct transformation and loads object type data to super type (type that Amazon Redshift uses to support JSON columns).
Also, I do not want to flatten the objects, just want to keep them as is. So dynamic_frame.relationalize() is also not a suitable solution.
Any help would be greatly thankful.
I was surprised to find that Cloud Datastream does not support enum data types in source if replicating from PostgreSQL.
Datastream doesn't support replication of columns of the enumerated (ENUM) data type.
As we have quite a few fields created that way, that is not a viable option for us. Is any good workaround for this limitation?
From google issue tracker:
A workaround is to create a generated column which is of type text. DataStream will then sync the text column automatically and happily.
Also:
we're looking into adding support for ENUMs as part of our GA launch of the PostgreSQL source
I'm used to use Dataprep to recipe json and csv files from Cloud Storage, but today I tried to ingest a table from BigQuery and could not parametrize.
Is it possible to do that?
Here are some screenshots to illustrate my question:
The prefix that I need
The standard does not work
From Cloud Storage works
In order to ingest a table from BigQuery, you can directly create a Dataset with SQL. I am not sure on what you would like to achieve with the 'Search' input, but it does not accept regular expressions. So, the '*' would not be needed, and just writing 'event_', the interface will filter the matching entries.
I would like to automatically stream data from an external PostgreSQL database into a Google Cloud Platform BigQuery database in my GCP account. So far, I have seen that one can query external databases (MySQL or PostgreSQL) with the EXTERNAL_QUERY() function, e.g.:
https://cloud.google.com/bigquery/docs/cloud-sql-federated-queries
But for that to work, the database has to be in GCP Cloud SQL. I tried to see what options are there for streaming from the external PostgreSQL into a Cloud SQL PostgreSQL database, but I could only find information about replicating it in a one time copy, not streaming:
https://cloud.google.com/sql/docs/mysql/replication/replication-from-external
The reason why I want this streaming into BigQuery is that I am using Google Data Studio to create reports from the external PostgreSQL, which works great, but GDS can only accept SQL query parameters if it comes from a Google BigQuery database. E.g. if we have a table with 1M entries, and we want a Google Data Studio parameter to be added by the user, this will turn into a:
SELECT * from table WHERE id=#parameter;
which means that the query will be faster, and won't hit the 100K records limit in Google Data Studio.
What's the best way of creating a connection between an external PostgreSQL (read-only access) and Google BigQuery so that when querying via BigQuery, one gets the same live results as querying the external PostgreSQL?
Perhaps you missed the options stated on the google cloud user guide?
https://cloud.google.com/sql/docs/mysql/replication/replication-from-external#setup-replication
Notice in this section, it says:
"When you set up your replication settings, you can also decide whether the Cloud SQL replica should stay in-sync with the source database server after the initial import is complete. A replica that should stay in-sync is online. A replica that is only updated once, is offline."
I suspect online mode is what you are looking for.
What you are looking for will require some architecture design based on your needs and some coding. There isn't a feature to automatically sync your PostgreSQL database with BigQuery (apart from the EXTERNAL_QUERY() functionality that has some limitations - 1 connection per db - performance - total of connections - etc).
In case you are not looking for the data in real time, what you can do is with Airflow for instance, have a DAG to connect to all your DBs once per day (using KubernetesPodOperator for instance), extract the data (from past day) and loading it into BQ. A typical ETL process, but in this case more EL(T). You can run this process more often if you cannot wait one day for the previous day of data.
On the other hand, if streaming is what you are looking for, then I can think on a Dataflow Job. I guess you can connect using a JDBC connector.
In addition, depending on how you have your pipeline structure, it might be easier to implement (but harder to maintain) if at the same moment you write to your PostgreSQL DB, you also stream your data into BigQuery.
Not sure if you have tried this already, but instead of adding a parameter, if you add a dropdown filter based on a dimension, Data Studio will push that down to the underlying Postgres db in this form:
SELECT * from table WHERE id=$filter_value;
This should achieve the same results you want without going through BigQuery.
I need to migrate the tables from the BigQuery to the on-prem Postgres database.
How can I efficiently achieve that?
Some thoughts that are coming
I will use Google APIs to export the data from the tables
Store it locally
And finally, import to Postgres
But I am not sure if that can be done for a huge amount of data in TBs. Also, how can I automate this process? Can I use Jenkins for that?
Exporting the data from BigQuery, store it and importing it to PostgreSQL is a good approach. Here are other two alternatives that you can consider:
1) There's a PostgreSQL wrapper for BigQuery that allows to query directly from BigQuery. Depending on your case scenario this might be the easiest way to transfer the data; although, for TBs it might not be the best approach. This suggestion was made by #David in this SO question.
2) Using Dataflow. You can create a ETL process using Apache Beam to made the transfer. Take a look at this how-to for transferring data from BigQuery to CloudSQL. You would need to adapt it for local PostgreSQL, but the idea maintains.
Here's another SO answer that gives more context on this approach.