Skip to main content

Facebook's Presto

By Anonymous
Listen:
In November 2013 Facebook published their Presto engine as Open Source, available at GitHub. Presto is a distributed interactive SQL query engine, able to run over dozens of modern BigData stores, based on Apache Hive or Cassandra. Presto comes with a limited JDBC Connector, supports Hive 0.13 with Parquet and Views.

Installation

Just a few specialties. Presto runs only with Java7, does not support Kerberos and does not have built-in user authentication, neither. To protect data a user should not be able to read, the use of HDFS Acl's / POSIX permissions should be considered. The setup of Presto is pretty easy and well documented. Just follow the documentation, use "uuidgen" to generate a unique ID for your Presto Node (node.id in node.properties) and add "hive" as datasource (config.properties: datasources=jmx,hive). I used user "hive" to start the server with:
export PATH=/usr/jdk64/jdk1.7.0_45/bin:$PATH && presto-server-0.68/bin/launcher start

After the successful start you should be able to connect to Presto's Webinterface (discovery.uri in config.properties). The UI is pretty simple, but a good point to see what happens with your queries, how many splits are created and what time each step takes.

The CLI is a stand-alone self-executing jar file and can be placed on any computer which has installed Java7 and can connect to the Presto Instance. To be sure that the client is using the correct Java version a PATH inclusion may make sense:
export PATH=/usr/jdk64/jdk1.7.0_45/bin:$PATH && /software/presto --server [your-presto-server]:[port] --catalog hive --schema default

presto:default> show tables;
    Table
--------------
 building
 hvac
 sample_07
 sample_08
 transactions

Now let's test if Presto is really fast and can compare with Impala. To make the tests more simple I wrote a small script which uses MR to generate sample data. Its available in my git-repo. Just run it as the user you want to be, maybe make it executable or use "sh". With the script I mentioned before I created a table called transactions, and this table we want to query. I post only 2 exemplary queries, but the script has a few more.

1. Finding highest gainers

select id, sum(amount) as amount from (select sender as id, amount * -1 as amount from transactions union all select recipient as id, amount from transactions) unionResult group by id order by amount desc limit 10;

Results
Hive: 39.078 seconds, Fetched: 10 row(s)
Tez: 18.227 seconds, Fetched: 10 row(s)
Presto: 0:02 [1.2M rows, 38.2MB] [720K rows/s, 22.9MB/s]

2. Finding fraudsters

select count(*) from (select a.sender, a.recipient, b.recipient as c from transactions a join transactions b on a.recipient = b.sender where a.time < b.time and b.time - a.time < 5) i;

Results
Hive: 208.065 seconds, Fetched: 1 row(s)
Tez: 101.758 seconds, Fetched: 1 row(s)
Presto: 1:02 [600K rows, 19.1MB] [9.7K rows/s, 317KB/s]

Conclusion

Since Tez brings a significant better performance, Presto brings light speed into Hadoop based SQL and can be measured with Impala. The advantage of Presto is the flexibility of connectors - the Presto Team will add more connectors for Oracle, MySQL, PostgresSQL and HBase very soon. Also Authentication (Kerberos), Authorization and SQL Grants will be supported within the next month [1].

Labels:

Comments

  1. jeet01 June, 2014

    Thanks .. Can you please help me ...i hv installed presto in 2 nodes...but still when execute query, it shows running on 1 node. why so. Plz help

    ReplyDelete
  2. Anonymous10 June, 2014

    You need one PrestoServer, and on all other nodes you need the Discovery Service: http://prestodb.io/docs/current/installation/discovery.html

    Note, all nodes need a unique ID.

    ReplyDelete

Post a Comment

Popular posts from this blog

Why Is Customer Obsession Disappearing?

By
 It's wild that even with all the cool tech we've got these days, like AI solving complex equations and doing business across time zones in a flash, so many companies are still struggling with the basics: taking care of their customers.The drama around Coinbase's customer support is a prime example of even tech giants messing up. And it's not just Coinbase — it's a big-picture issue for the whole industry. At some point, the idea of "customer obsession" got replaced with "customer automation," and now we're seeing the problems that came with it. "Cases" What Not to Do Coinbase, as main example, has long been synonymous with making cryptocurrency accessible. Whether you’re a first-time buyer or a seasoned trader, their platform was once the gold standard for user experience. But lately, their customer support practices have been making headlines for all the wrong reasons: Coinbase - Stuck in the Loop:  Users have reported being caugh...
Post a Comment
Read more

MySQL Scaling in 2024

By
When your MySQL database reaches its performance limits, vertical scaling through hardware upgrades provides a temporary solution. Long-term growth, though, requires a more comprehensive approach. This involves optimizing the database strategically and integrating complementary technologies. Caching The implementation of a caching layer, such as Memcached or Redis , can result in a notable reduction in the load and an increase ni performance at MySQL. In-memory stores cache data that is accessed frequently, enabling near-instantaneous responses and freeing the database for other tasks. For applications with heavy read traffic on relatively static data (e.g. product catalogues, user profiles), caching represents a low-effort, high-impact solution. Consider a online shop product catalogue with thousands of items. With each visit to the website, the application queries the database in order to retrieve product details. By using caching, the retrieved details can be stored in Memcached (a...
Post a Comment
Read more

Deal with corrupted messages in Apache Kafka

By
Under some strange circumstances, it can happen that a message in a Kafka topic is corrupted. This often happens when using 3rd party frameworks with Kafka. In addition, Kafka < 0.9 does not have a lock on Log.read() at the consumer read level, but does have a lock on Log.write(). This can lead to a rare race condition as described in KAKFA-2477 [1]. A likely log entry looks like this: ERROR Error processing message, stopping consumer: (kafka.tools.ConsoleConsumer$) kafka.message.InvalidMessageException: Message is corrupt (stored crc = xxxxxxxxxx, computed crc = yyyyyyyyyy Kafka-Tools Kafka stores the offset of each consumer in Zookeeper. To read the offsets, Kafka provides handy tools [2]. But you can also use zkCli.sh, at least to display the consumer and the stored offsets. First we need to find the consumer for a topic (> Kafka 0.9): bin/kafka-consumer-groups.sh --zookeeper management01:2181 --describe --group test Prior to Kafka 0.9, the only way to get this in...
Post a Comment
Read more