I am using Twitter Steaming and wanted to do visualization for my data. Which is the most compatible and feature enriched database recommended?
You could setup a data pipeline where you fetch and move your data using a tool like Apache Flume or/and Apache Kafka, analyze it with Spark and store it in a sink like Elasticsearch (or any other NoSql db). After that you can query your data using a visualization tool like Kibana.
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I am trying to migrate Cassandra cluster onto AWS Keyspaces for Apache Cassandra.
After the migration is done how can I verify that the data has been migrated successfully as-is?
Many solutions are possible, you could simply read all rows of a partition and compute a checksum / signature and compare with your original data for instance.Then iterating through all your partitions, then doing it for all your tables. Checksums work.
You could use AWS Glue to perform an 'except' function. Spark has a lot of usefull functions for working with massive datasets. Glue is serverless spark. You can use the spark cassandra connector with Cassandra and Keyspaces to work with datasets in glue. For example you may want to see the data that is not in Keyspaces.
cassandraTableDataframe.except(keyspacesTableDateframe).
You could also do this by exporting both datasets to s3 and performing these queries in Athena.
Here is a helpful repository of Glue and Keyspaces functions including export, count, and distinct.
My team is trying to integrate datadog's RUM data into Snowflake for our data scientists to consume. Is this possible? If so how?
So far I have found documentation on how to integrate data from snowflake into the datadog dashboard, but not the other way around.
There are a number of options:
Use an ETL tool that can connect to both Snowflake and Datadog
Bulk load: export the data to an S3 (or similar) file and use the Snowflake COPY INTO command
Streaming: stream the data out of Datadog and then into Snowflake using Snowpipe
Poll the RUM events API with an application you develop yourself.
https://docs.datadoghq.com/api/latest/rum/
Write microbatches to your target tables using one of the language connectors, or the Spark connector.
https://docs.snowflake.com/en/user-guide/spark-connector-use.html
is it possible to connect Apache Kylin without other databases like Hbase (plus HDFS) in general? So you can store raw data and the cube metadata somewhere else?
I think you coulde use Apache Hive using managed native tables
(Hive storage handlers)
Hive could connect over ODBC driver to MySQL for example
To use Kylin ,HDFS is mandatatory .Raw data as well as Cube data both will be stored in HDFS.
If you want to support other nosql datastore like cassandra ,you can consider other framework ,FiloDB
I am currently doing an app that loads data into HBase, I chose HBase because the data is not structured and therefore using a column based database is recommended.
Once the data is in HBase I thought of integrating Solr to it but I found little information about the subject and no answer for my question "https://stackoverflow.com/questions/36542936/integrating-solr-to-hbase"
So I wanted to ask how I can query data stored in HBase? Spark Streaming doesn't seem to be made for that ..
Any help please ?
Thanks in advance
Assuming that your question is on how to query data from Hbase.
Apache Phoenix Provides a Sql Wrapper over Hbase.
Hive Hbase Integration Hive also provides a Sql Wrapper over Hbase
Spark Hbase Plugin lets your Apache Spark application interact with Apache HBase.
In a current application, we retain all requests in a SQL Server database table. Since we will be moving to ElasticSearch, can I simply just serialize the data entry (creating the JSON object representation) and throwing that into an ElasticSearch type to be used for a Kibana dashboard?
You do not need to use Logstash to ingest the data into Elasticsearch. Logstash
is simply a tool used to read data from a location, transform it, and then write
it to an output.
You can always write something yourself, or use a different tool to get the data
from your SQL database into Elasticsearch. Once in Elasticsearch, Assuming it is
inserted in a proper manner, Kibana will be able to read it.