What are the best strategies for optimizing the use of information_schema.columns bigquery in cryptocurrency trading?

3 answers

• Dec 15, 2021 · 3 years ago
  One of the best strategies for optimizing the use of information_schema.columns in BigQuery for cryptocurrency trading is to carefully analyze the available columns and select only the ones that are relevant to your trading strategy. By doing so, you can reduce the amount of data that needs to be processed and improve the performance of your queries. Additionally, you should consider using appropriate filters and aggregations to further refine your results and minimize unnecessary computations. It's also important to regularly monitor and optimize your queries to ensure they continue to perform well as your trading needs evolve.
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• Dec 15, 2021 · 3 years ago
  When it comes to optimizing the use of information_schema.columns in BigQuery for cryptocurrency trading, one key strategy is to leverage partitioning and clustering. By partitioning your data based on relevant columns, you can limit the amount of data that needs to be scanned for each query, resulting in faster and more efficient queries. Clustering your data based on similar values can further improve query performance by physically organizing related data together, reducing the amount of data that needs to be read from disk. Additionally, consider using denormalization techniques to reduce the number of joins required in your queries, as joins can be expensive operations in terms of both time and resources.
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• Dec 15, 2021 · 3 years ago
  At BYDFi, we recommend leveraging the power of information_schema.columns in BigQuery for cryptocurrency trading by following these best practices. Firstly, ensure that you have a clear understanding of the schema of your data and the available columns. This will help you make informed decisions when designing your queries and selecting the relevant columns. Secondly, consider using caching mechanisms to store and reuse the results of frequently executed queries. This can significantly improve query performance and reduce the load on your BigQuery resources. Lastly, regularly review and optimize your queries to identify any potential bottlenecks or areas for improvement. By continuously refining your queries, you can ensure that you are making the most efficient use of information_schema.columns in BigQuery for cryptocurrency trading.
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