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Searches (and general querying) with HBase and/or Cassandra (best practices?)


Searches (and general querying) with HBase and/or Cassandra (best practices?)

By : adamov
Date : January 10 2021, 01:45 PM
this one helps. Being able to query properties directly is one of the features you lose when moving away from SQL, so you need a way to maintain your own index to let you find records.
If your datastore does not have built in indexing or atomic list operations, you will need to deal with the locking issues you mention. However, indexing doesn't necessarily need to be synchronous - maintain a queue of updated records to be reindexed and you have a solution for 3 that can be reused to solve 2 also.
code :


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Which SEO practices are likely to be responsible for SO questions appearing so quickly in Google searches?

Which SEO practices are likely to be responsible for SO questions appearing so quickly in Google searches?


By : Adi
Date : March 29 2020, 07:55 AM
hope this fix your issue To put it simply, more popular websites with more quality content and more frequent changes are ranked higher with Google's algorithm, and are indexed and cached more frequently than sites that are less popular or change less frequently.
General strategy for complex multi-stage searches

General strategy for complex multi-stage searches


By : user2462390
Date : March 29 2020, 07:55 AM
wish of those help I've done this by keeping search performance counters in a table. Basically monitoring the average percentage of rows that the search filters and the run time.
I then create a performance figure based on TotalNumberOfRowsToSearch * Percent_Not_Matched / RunTimeInSeconds This figure is a direct correlation of rows per second it can filter out. Averaged over thousands of runs, it is a rather good prediction.
best practices for text-based searches in database

best practices for text-based searches in database


By : Haluk Cenikli
Date : March 29 2020, 07:55 AM
Hope this helps There's no need to use two fields for this, one would be enough. A field has two "values", one stored that can be retrieved using Document.Get(...), and one indexed that's used for searching. It's not technically required to store the values either, a common solution is to store a id that's used to lookup the original content in a database. This would also allow you to lookup more information, like author information and document location.
Lucene.Net would help in this case, but it requires you to write the infrastructure yourself. You would need to take care of configuring analyzers (usually nothing to configure), and index your content. As mention in a comment, you could go for SQL Server's Full Text Search functionality, but that itself has some limitations (which may not affect you).
What is the best practice for implementing low cardinality searches in Cassandra

What is the best practice for implementing low cardinality searches in Cassandra


By : Leo Nickel
Date : March 29 2020, 07:55 AM
help you fix your problem Assume that I have the following table CQL (well a fragment of the table): , I would recommend a table like
code :
CREATE TABLE order_by_status (
  order_id UUID,
  placed timestamp,
  status text,
  PRIMARY KEY ((status), order_id)
)
CREATE TABLE order_by_status (
  order_id UUID,
  placed timestamp,
  bucket text,
  status text,
  PRIMARY KEY ((status, bucket), order_id)
)
realtime querying/aggregating millions of records - hadoop? hbase? cassandra?

realtime querying/aggregating millions of records - hadoop? hbase? cassandra?


By : Dots42
Date : March 29 2020, 07:55 AM
should help you out Hive or Pig don't seem like they would help you. Essentially each of them compiles down to one or more map/reduce jobs, so the response cannot be within 5 seconds
HBase may work, although your infrastructure is a bit small for optimal performance. I don't understand why you can't pre-compute summary statistics for each column. You should look up computing running averages so that you don't have to do heavy weight reduces.
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