Maybe they can finally write some docs
Ha!
Elasticsearch Raises $70 Million
61–67 of 67 posts
Re: Elasticsearch Raises $70 Million
#62Maybe they can finally write some docs
The docs are pretty good and have been for a while:
http://www.elasticsearch.org/guide/
Admittedly they were pretty poor early on, but they've matured with the product.
Re: Elasticsearch Raises $70 Million
#63Earlier quoted context omitted.
* Kibana on ElasticSearch. This is huge. You get a polished Search & Graphing UI with very little effort. * Much more approachable config. * Its clustering is easier to setup. * Eventhough logstash is a bit heavy for my taste, the whole ELK stack is really nice for aggregating server logs.
Re: logstash too heavy That's what logstash-forwarder[1] (formerly lumberjack) is for. It's in Go, not Java. [1] https://github.com/elasticsearch/logstash-forwarder
I use beaver, which is a python variant of the logstash agent
Re: Elasticsearch Raises $70 Million
#64Earlier quoted context omitted.
Open-source is becoming the only way to develop (and, especially , maintain) complex software. The fact that the engineers can gain employer-independent reputations gives them an incentive that's astronomically expensive (as hedge fund compensation goes) to replicate otherwise. The world is finally figuring out that it's impossible to employ top talent, but that it can be quite lucrative to sponsor it.
It's not impossible to employ top talent. That is a very ignorant statement.
Better to say it's impossible to keep top talent around for more than a couple of years. Once they start to get bored they leave.
Re: Elasticsearch Raises $70 Million
#65I'm sitting in Elasticsearch training right now (during a caffeine break). These are some really great guys that know their stuff, and they're committed to contributing back to the OSS version everything that makes sense. They contribute a ton of code back to Lucene and employ a lot of the brightest minds in this space. On the product side, I'm sitting here being amazed at some of the problems they've solved very ele…
How is it better than Solr? I havent looked at Elastic Search in a long time, so I really do want to know. Not trying to pick a fight. ;)
Honestly I'm not sure, I haven't used Solr. I was just comparing it to the relational databases I've used, key-value stores like Cassandra, and other documents stores like Mongo. It definitely doesn't replace relational stores, but IMO blows all of the other NoSQL data stores out of the water. The Lucene indexing behind the scenes just really delivers some impressive functionality.
Re: Elasticsearch Raises $70 Million
#66Elasticsearch is great. I have spent the last 6 months working on a project using it as the primary search technology, it has been nothing but great. I have not had any training and tried to figure it out through the online docs (which in the last overhaul have gotten much better) so forgive me if any of what I'm about to say is wrong, or better yet please correct me so I can learn :)
here's the things I noticed when using it: - Since it's schemaless by default it will guess the data type of a document based on the first value it sees, as far as I'm aware you're not able to change a data type later on, so I found it best to create a schema (aka mapping) being explicit about the fields data types up front. I think explicit is better anyway (Zen of python ;) )
- It's blazingly fast. Like crazy quick.
- Use the geo data type if you're going to be doing radius queries. I've got 50M documents in the index and it queries insanely fast. It's been just as fast as PostGIS (which I also love)
- Use this as the GUI: http://mobz.github.io/elasticsearch-head/
- Do some proper research on filtering before you start, start here: http://www.elasticsearch.org/guide/en/elasticsearch/referenc...
the correctly configured snowball filter will make sure things like "rückwärts" will match "ruckwarts",
Re: Elasticsearch Raises $70 Million
#67Earlier quoted context omitted.
Want to highlight some of your specific pain points?
I guess I'm in the minority based on the other comments here… After spending a few hours with the documentation, I felt like I had a generally good feel for how you would interact with ES through curl, but then jumping into using the Ruby library there seemed to be a big leap and I felt like I needed to have a much more intimate knowledge of how ES worked to "get" it. A lot of guess and check before I figured out how…
I found the elasticsearch tutorials on youtube by Clinton Gormley pretty helpful in understanding the concepts. Also came across this book (which I haven't really read so I don't know how good it is, just posting it here)
http://exploringelasticsearch.com/