I need to setup a data pipeline from some source databases like Oracle, MySQL and load the data to BigQuery.
How can I use google-cloud-dataflow to read data from a database(jdbc connection) and write to BigQuery tables using Python.
Also, I have some hive tables in an on-premise Hadoop cluster, how do I transfer this data to BigQuery.
I couldn't find the right documentation or examples to achieve this.
Can you please point me in the right direction.
I applied a solution in my project to provide such thing, you need to follow these steps:
Load data from Google Cloud SQL to Google Cloud storage in CSV by following this link.
Load the CSV data from Google cloud storage directly into BigQuery by following this link.
Related
Our organization has data in Google Bigtable - hosted by our Vendor. We want to run jobs in BigQuery to query from Bigtable and export the data to CloudStore as .csv files without the storing the data as a dataset in BigQuery.
We do not want to store in BigQuery datasets as we are not doing any analysis using BigQuery as all Analysis is done using on premise Analytical solution.
Is this possible ?
You have a few options, and the best solution would be to automate using Cloud Workflows.
The steps I see would be:
Export from BigTable in Avro or Parquet format to Cloud Storage.
There is a gcloud and API way to do this described here.
You then import the exported files into BigQuery.
There is a a way to use bq CLI tool and API way as well to do this described here.
Then you export from BigQuery to multiple CSV files as it's documented here.
You get multiple CSV files, you can then run the gcloud compose tool to merge them.
All the above can be done in Cloud Workflows. Each call can be implemented either via API (preferred) or using the command line options using Cloud Build triggers for example. For Workflow syntax you can get guidance from this article, and the linked content from the footer section of the article.
I want to load many tables which is in aws rds mysql server by using cloud data fusion. each table storage is more than about 1gb. also I found the plugin which name is "multiple database table" to load multi table. but i got a fail. Also basically when I used database source I can check my tables' schema. However, in multiple database table, i can 't find how to check table's schema. how can i use this plugin? or is there any other way to load many tables in data fusion service?
My pipeline setting was as follows.
I'm posting this Community Wiki as OP didn't provide enough details to reproduce but the below information might help someone.
There are few ways to get your data using Cloud Data Fusion, you can use pipeline, plugin, driver and a few others depending on your needs.
On the internet you can find two very well described guides with examples.
If you would like to find some information about Cloud Data Fusion with GCP products you should read Bahadir Bulut guide - How I used Google Cloud Data Fusion to create a data warehouse - Part 1 and Part 2. Also Data Fusion allows to use 150+ preconfigured connectors and transformations like Amazons S3, SQS, etc. Azure services and many more.
Another well described (which I guess would help OP) is to configure both Amazon and GCP resources and using pipelines. This guide is Building a Simple Batch Data Pipeline from AWS RDS to Google BigQuery — Part 1: Setting UP AWS Data pipeline and second part Building a Simple Batch Data Pipeline from AWS RDS to Google BigQuery — Part 2: Setting up BigQuery Transfer Service and Scheduled Query.. In short this guide describes 2 main steps:
Extract data from MYSQL RDS and bring into S3 using AWS data pipeline service
From S3, bring the file inside Bigquery using BigqQuery transfer service.
My requirement is to migrate data from teradata database to Google bigquery database where table structure and schema remains unchanged. Later, using the bigquery database, I want to generate reports.
Can anyone suggest how I can achieve this?
I think you should try TDCH to export data to Google Cloud Storage in Avro format. TDCH runs on top of hadoop and exports data in parallel. You can then import data from avro files into BigQuery.
I was part of a team that addressed this issue in a Whitepaper.
The white paper documents the process of migrating data from Teradata Database to Google BigQuery. It highlights several key areas to consider when planning a migration of this nature, including the rationale for Apache NiFi as the preferred data flow technology, pre-migration considerations, details of the migration phase, and post-migration best practices.
Link: How To Migrate From Teradata To Google BigQuery
I think you can also try to use cloud composer(apache airflow) or install apache airflow in instance.
If you can open the ports from Teradata DB then you can run 'gsutil' command from there and schedule it via airflow/composer to run the jobs on daily basis. Its quick and you can leverage the scheduling capabilities of airflow.
BigQuery introduced Migration Service which is a comprehensive solution for migrating the data warehouse to BigQuery. It includes free to use tools that help with each phase of migration including assessment and planning to execution and verification.
Reference:
https://cloud.google.com/bigquery/docs/migration-intro
I am new in NoSql,I want to migrate SQL data into NoSQL from one cloud to another cloud using JSON file or is there any other way to perform migration ..please advice!
People, the company where I work has some MySQL databases on AWS (Amazon RDS). We are making a POC with BigQuery and what I am researching now is how to replicate the bases to BigQuery (the existing registers and the new ones in the future). My doubts are:
How to replicate the MySQL tables and rows to BigQuery. Is there any tool to do that (I am reading about Amazon Database Migration Service)? Should I replicate to Google Cloud SQL and than export to BigQuery?
How to replicate the future registers? Is possible to create a job inside MySQL to send the new registers after a predefined number? For example, after 1,000 new rows are inserted (or a time is passed), some event is "triggered" and the new registers are copied to Cloud SQL/BigQuery?
My initial idea is to dump the original base, load it to the other and use a script to listen to new registers and send them to the new base.
Have I explained it properly? Is it understandable?
You will need to use one of the ETL tools which have integration with both mySQL and BigQuery to perform initial transfer of the data and copy subsequent changes to BigQuery. Take a look on the list of available tools [1]
You can also implement your own tool by developing a process which will extract the data from mySQL to a CSV file and then load that file into BigQuery using data import [2]
[1] https://cloud.google.com/bigquery/third-party-tools
[2] https://cloud.google.com/bigquery/loading-data-into-bigquery
In addition to what Vadim said, you can try:
mysqldump to CSV files to s3 (I believe RDS allows that)
run "gsutil" Google Cloud Storage utility to copy data from s3 to GCS
run "bq load file.csv" to load the file to BigQuery
I'm interested in hearing your experience, so feel free to ping me in private.