I'm looking for a tool to load CSV into Cassandra. I was hoping to use RazorSQL for this but I've been told that it will be several months out.
What is a good tool?
Thanks
1) If you have all the data to be loaded in place you can try sstableloader(only for cassandra 0.8.x onwards) utility to bulk load the data.For more details see:cassandra bulk loader
2) Cassandra has introduced BulkOutputFormat bulk loading data into cassandra with hadoop job in latest version that is cassandra-1.1.x onwards.
For more details see:Bulkloading to Cassandra with Hadoop
I'm dubious that tool support would help a great deal with this, since a Cassandra schema needs to reflect the queries that you want to run, rather than just being a generic model of your domain.
The built-in bulk loading mechanism for cassandra is via BinaryMemtables: http://wiki.apache.org/cassandra/BinaryMemtable
However, whether you use this or the more usual Thrift interface, you still probably need to manually design a mapping from your CSV into Cassandra ColumnFamilies, taking into account the queries you need to run. A generic mapping from CSV-> Cassandra may not be appropriate since secondary indexes and denormalisation are commonly needed.
For Cassandra 1.1.3 and higher, there is the CQL COPY command that is available for importing (or exporting) data to (or from) a table. According to the documentation, if you are importing less than 2 million rows, roughly, then this is a good option. Is is much easier to use than the sstableloader and less error prone. The sstableloader requires you to create strictly formatted .db files whereas the CQL COPY command accepts a delimited text file. Documenation here:
http://www.datastax.com/docs/1.1/references/cql/COPY
For larger data sets, you should use the sstableloader.http://www.datastax.com/docs/1.1/references/bulkloader. A working example is described here http://www.datastax.com/dev/blog/bulk-loading.
Related
I am very new to Cassandra and any help here would be appreciated. I have a cluster of 6 nodes that spans 2 datacenters (3 nodes to each cluster). My client has decided that they do not want to renew their Cassandra license with Datastax anymore and want their data exported into a format that can be easily imported into another Database in the future. I was thinking of exporting the data as a CSV file, but since the data is distributed between all the nodes, I am not sure what is the best way to export all the data.
One option - You should be able to use the CQL COPY command - which copies the data into a CSV format. The nice thing about copy is that you can run it from a single node (i.e. it is not a "node" level tool). Command would be (once in cqlsh):
CQL> COPY . to '/path/to/file'
If there is a LOT of data, or a lot of tables, this tool may not be a great fit. But for small number of tables that don't have HUGE rowcounts (< several million), this works well. Hope that helps.
-Jim
Since 2018 you can use DSBulk with DSE to export or import data to/from CSV (by default), or JSON. Since the end of 2019 it's possible to use it with open source Cassandra as well.
It could be as simple as:
dsbulk unload -k keyspace -t table -u user -p password -url filename
DSBulk is heavily optimized for fast data export, without putting too much load onto the coordinator node that happens when you just run select * from table.
You can control what columns to export, and even provide your own query, etc. DataStax blog has a series of blog posts about different aspects of using DSBulk:
Introduction and Loading
More Loading
Common Settings
Unloading
Counting
Examples for Loading From Other Locations
You can use CQL COPY command for exporting the data from Cassandra cluster. However it is performant for small set of data if you are having big size of data this command is not useful cause it will give some error or timeout issue. Also, you may use sstabledump and export your node-wise date into JSON format. Hope, this will useful for you.
I have implemented small script for this purpose. It isn't the best way, since it slow and, in my experience, produces connection errors on system tables. But it could be useful for inspecting Cassandra on small datasets: https://github.com/kirillt/cassandra-utils
How can I export data, over a period of time (like hourly or daily) or updated records from a Cassandra database? It seems like using an index with a date field might work, but I definitely get timeouts in my cqlsh when I try that by hand, so I'm concerned that it's not reliable to do that.
If that's not the right way, then how do people get their data out of Cassandra and into a traditional database (for analysis, querying with JOINs, etc..)? It's not a java shop, so using Spark is non-trivial (and we don't want to change our whole system to use Spark instead of cassandra directly). Do I have to read sstables and try to keep track of them that way? Is there a way to say "get me all records affected after point in time X" or "get me all changes after timestamp X" or something similar?
It looks like Cassandra is really awesome at rapidly reading and writing individual records, but beyond that Cassandra seems to not be the right tool if you want to pull its data into anything else for analysis or warehousing or querying...
Spark is the most typical to do exactly that (as you say). It does it efficiently and is used often so pretty reliable. Cassandra is not really designed for OLAP workloads but things like spark connector help bridge the gap. DataStax Enterprise might have some more options available to you but I am not sure their current offerings.
You can still just query and page through the whole data set with normal CQL queries, its just not as fast. You can even use ALLOW FILTERING just be wary as its very expensive and can impact your cluster (creating a separate dc for the workload and using LOCOL_CL queries against it helps). You will probably also in that scenario add a < token() and > token() to the where clause to split up the query and prevent too much work on any one coordinator. Organizing your data so that this query is more efficient would be strongly recommended (ie if doing time slices, put things in a partition bucketed by time and clustering key timeuuids so its sequential read for each part of time).
Kinda cheesy sounding but the CSV dump from cqlsh is actually fast and might work for you if your data set is small enough.
I would not recommend going to the sstables directly unless you are familiar with internals and using hadoop or spark.
I have requirement to update existing values in Cassandra 3.0 to Uppercase.
Its for all rows and for a single column of type text
I would need to do this update all the way to production and want the least intrusive/ iterative way of doing it as some of environment will be update by different team. This will be a one time task
Thanks for help,Appreciate your time
Neha
Cassandra Newbie
Cassandra does not offer native support for this kind of work. You will need to look at either writting your own application that reads and re-insert with upercase. For large scale cluster, you will want to look at using spark on cassandra. Spark is often use on top of Cassandra to perform some analytics, or data migration, like you are doing.
I have to change the schema of one of my tables in Cassandra. It's cannot be done by simply using ALTER TABLE command, because there are some changes in primary key.
So the question is: How to do such a migration in the best way?
Using COPY command in cql is not an option in here because dump file can be really huge.
Can I solve this problem by not creating some custom application?
Like Guillaume has suggested in the comment - you can't do this directly in cassandra. Schema altering operations are very limited here. You have to perform such migration manually using one of suggested there tools OR if you have very large tables you can leverage Spark.
Spark can efficiently read data from your nodes, transform them locally and save them back to db. Remember that such migration requires reading whole db content, so might take a while. It might be the most performant solution, however needs some bigger preparation - Spark cluster setup.
we are going to create a new project on cassandra with php or java.
As we estimated, there will be 20K req/sec to cassandra cluster.
Specially wide column feature is important for this project, but i can not make it clear: should i prefer thrift API or CQL3 library like php-driver etc?
There is an post that says 'Thrift API is not going to be getting new features' in this link. So i am not sure about thrift.
if i decided to use cql3, i have to alter table to be sure column exists before all insert queries like this, which is discussed at here. i think this will be a performance issue for me.
So which of them is best to my case ?
Thrift is a legacy interface in Cassandra. All new development should use the native CQL interface.
I'm not clear on why you think you'd need to do an alter table frequently. Typically you would define a schema once and rarely if ever use alter table.