Parallelized loading of data into Pandas Dataframes [duplicate]

By -

I need to compare data from 2 azure databases, that each contain fair amount of data. Given that the sql query is i/o bound, I am wondering if I could kick off 2 queries (one to each database) concurrently, and have the returned data deposited into the respective 2 dataframes.

I have read that Pandas is not thread-safe (this is really unfortunate) otherwise the Python ThreadPoolExecutor along with Pandas pd.read_sql could handle it. Now a few questions:

  1. is it still true that Pandas is still not threadsafe ?
  2. is there a better library to use that is thread-safe ?
  3. other thought on how to safely improve the performance of getting data into dataframes on my PC ? (using python)


Comments

Post a Comment

Popular posts from this blog

Today Walkin 14th-Sept

By -
Image
14th Sept 2017 ( GO Through all List) Read Walkin details properly , Try to call company before attending if possible !!! ==================================== 1. Myntra through fresherworld (Call Based , Venue shared to shortlisted candidates) _____________________________ 2. Magna : Hiring for Client Harman : C++
Read more

Spring Elasticsearch Operations

By -
Elasticsearch Operations Spring Data Elasticsearch uses two interfaces to define the operations that can be called against an Elasticsearch index. These are ElasticsearchOperations and ReactiveElasticsearchOperations. Whereas the first is used with the classic synchronous implementations, the second one uses reactive infrastructure. The default implementations of the interfaces offer: Read/Write mapping support for domain types. A rich query and criteria api. Resource management and Exception translation. ElasticsearchTemplate The ElasticsearchTemplate is an implementation of the ElasticsearchOperations interface using the Transport Client. @Configuration public class TransportClientConfig extends ElasticsearchConfigurationSupport {   @Bean   public Client elasticsearchClient() throws UnknownHostException {                      Settings settings = Settings.builder().put("cluster.name", "elasticsearch")....
Read more

Hibernate Search - Elasticsearch with JSON manipulation

By -
Elasticsearch with JSON manipulation Elasticsearch ships with many features. It is possible that at some point, one feature you need will not be exposed by the Search DSL. To work around such limitations, Hibernate Search provides ways to: Transform the HTTP request sent to Elasticsearch for search queries. Read the raw JSON of the HTTP response received from Elasticsearch for search queries. Direct changes to the HTTP request may conflict with Hibernate Search features and be supported differently by different versions of Elasticsearch. Similarly, the content of the HTTP response may change depending on the version of Elasticsearch, depending on which Hibernate Search features are used, and even depending on how Hibernate Search features are implemented. Thus, features relying on direct access to HTTP requests or responses cannot be guaranteed to continue to work when upgrading Hibernate Search, even for micro upgrades (x.y.z to x.y.(z+1)). Use this at your own risk....
Read more