PhoenixCon 2017

Apache Phoenix

Please join us for PhoenixCon 2017, the 2nd annual <A TITLE="Apache Phoenix" HREF="http://phoenix.apache.org/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Apache Phoenix</A> conference, the day after HBaseCon, to hear from committers and users alike on all things Apache Phoenix. Lunch will be provided and we'll conclude with a happy hour.
 
<TABLE STYLE="width: 100%; border: 1px solid #000000; border-collapse: collapse;"><CAPTION>
Conference Schedule
</CAPTION>
<TBODY>
<TR>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Time</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Title</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Speaker</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Affiliation</TD>
</TR>
<TR STYLE="background-color: #f5f5f5;">
<TD STYLE="border: 1px solid #000000; padding: 5px;">10:30</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Welcome</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">James Taylor</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Salesforce</TD>
</TR>
<TR>
<TD STYLE="border: 1px solid #000000; padding: 5px;">11:00</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;" TITLE="Phoenix is in wide use at Salesforce, and a great help when we build features on HBase. The team that builds the Chatter product has been an early adopter. This talk will look at some of the different ways we use hbase and how Phoenix helped us succeed. We’ll show queries and the resulting plans, and share some perf numbers too. 

Here are the use cases we'll look at: 
* Accumulating event signals into a social graph: easy data definition and insertion 
* Using the social graph to improve the quality of type-ahead proposals for user mentions: fast scans 
* Services to accumulate counts and uniquified sets from incoming events: handling concurrency 
* Feed composition at write time to optimize read time performance: secondary indexes and eventual consistency">Phoenix Use Cases in the Salesforce Chatter Product</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Gary Horen, Matthew Van Wely</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Salesforce</TD>
</TR>
<TR>
<TD STYLE="border: 1px solid #000000; padding: 5px;">11:45</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;" TITLE="Storage formats are a new feature introduced in Phoenix 4.10 that enables reducing the disk size of tables which also improves performance. 
The column mapping feature allows us to use numbers instead of column names as HBase column qualifiers. This improves performance by allowing us to derive the ordinal position from the column qualifier of a cell to perform a lookup in the sorted list of cells returned by HBase. We can also do fast DDL operations like column rename and metadata level column drops on tables. As these number based qualifiers are generally smaller (1 to 4 bytes) than column names, the disk size of tables is smaller which improves performance for most queries. 
The immutable data encoding feature packs all column values of a column family into a single HBase cell. Column values are serialized into a byte array with the offsets stored at the end. Enabling this feature on a table improves upsert times and decrease count queries and queries that filter or group by on non-pk columns. 
We recommend enabling the column mapping feature unless you expect the number of columns in a table (and also its views) to exceed 2147483647. Also the Immutable Data Encoding feature is recommended when the data is sufficiently dense (about 50% of columns have values), with growing sparseness the overhead of storing offset information negatively affects performance. With the default HBase block size of 64K, performance starts to degrade once the size of the packed cell exceeds 50 KB. We do not recommend using this feature for immutable tables that have views because of the way column qualifiers are assigned for columns in views which makes data sparse (especially when columns are added to views).">Column Mapping and Immutable Data Encoding</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Thomas D'Silva, Samarth Jain</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Salesforce</TD>
</TR>
<TR STYLE="background-color: #f5f5f5;">
<TD STYLE="border: 1px solid #000000; padding: 5px;">12:30</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;" COLSPAN="3">Lunch</TD>
</TR>
<TR>
<TD STYLE="border: 1px solid #000000; padding: 5px;">1:15</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;" TITLE="Apache Phoenix supports two kinds of secondary indexes, global and local to provide orthogonal way to access data from its primary access path. A Local secondary index is 'local' in the sense that region wise data is indexed and the index data is co-reside in the same region but different column family/families. Local indexes are very useful for the write heavy, space constrained use cases and helpful for the systems require many alternative access paths than primary key and 100% consistent view of the base table. In this talk we discuss more about architecture, data model, how 100% atomic and how 'local' nature helps to keep the same write performance even with multiple indexes present in the system.">Local secondary indexes in Apache Phoenix</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Rajeshbabu Chintaguntla</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Hortonworks</TD>
</TR>
<TR>
<TD STYLE="border: 1px solid #000000; padding: 5px;">2:00</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;" TITLE="Phoenix has seen a growing presence at Bloomberg, Supporting applications from diverse business areas with a multitude of access patterns. 
Phoenix helps us bridge the gap between Hbase and delivering the SQL simplicity to our Big Data developers. We would share some of our success stories and a few challenges while working with Apache Phoenix. 

We have been engaged in working with Cursors, Phoenix/hbase cross-DC replication, Calcite in Phoenix and Harden Phoenix. 

Harden Phoenix attempts to re-use the HBase test harnesses and port over the Hbase Big Link List tests to Apache Phoenix and perform the operations over a real cluster on a nightly basis to test features and track benchmarks per component. This process is still a work in progress and can been see on https://github.com/apache/phoenix/pull/245">Phoenix @Bloomberg and Harden Phoenix</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Anirudha Jadhav, Gabriel Jimenez</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Bloomberg</TD>
</TR>
<TR STYLE="background-color: #f5f5f5;">
<TD STYLE="border: 1px solid #000000; padding: 5px;">2:45</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;" COLSPAN="3">Break</TD>
</TR>
<TR>
<TD STYLE="border: 1px solid #000000; padding: 5px;">3:00</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;" TITLE="This talk will cover some new features being added to the Phoenix Query Server (PQS) and present a vision of the future with Apache Avatica. We will discuss metrics instrumentation being added to PQS that provides automatic insight into the performance of the system. We'll also present an in-progress load-balancer that provides both high availability and service discovery for PQS. Finally, we'll take a step back to envision an alternate reality where Avatica, the technology powering the Phoenix Query Server and its light-weight client driver, simplifies client applications to all of the databases that comprise an organization. We’ll describe a reality where classpath and dependency issues are a problem of the past with a universal client for users to access all kinds of JDBC-compatible databases.">Breaking the mold with the Phoenix Query Server</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Josh Elser, Rahul Shrivastava</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Hortonworks Salesforce</TD>
</TR>
<TR>
<TD STYLE="border: 1px solid #000000; padding: 5px;">3:45</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;" TITLE="Truecar needs to provide OEM Incentives to consumers. These incentives are time bound and based on zipcode(s) and member networks. Each incentive can be valid for any number of zipcode ranging from 1-40k. We also need to keep the historical data of Incentive for Analytics. 
To facilitate filtering on basis of zipcode, we used zipcode as column name. Then we used Dynamic Columns feature of Phoenix to query Incentives while leveraging NoSql nature of HBase. In Incentives table each row has columns ranging from 10-30K. Even with such wide rows we were able to get 3x performance boost from Phoenix/HBase solution as compared to our Elastic Search solution for Incentives. 
Along with Dynamic Columns, we also leveraged column families to group zipcodes and bloom filters for performance improvements. 

In this presentation, we would like to share our journey of migrating Incentives from Elastic Search to Phoenix/HBase while achieving better scalability and performance metrics.">Dynamic Columns for SQL on NoSql Data</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Anil Gupta, Amey Hegde</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Truecar </TD>
</TR>
<TR>
<TD STYLE="border: 1px solid #000000; padding: 5px;">4:30</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;" TITLE="Transaction processing is a critical service in databases that ensures that all data accesses satisfy the ACID properties. Traditionally, Phoenix has been using the Apache Tephra transaction processing technology. Recently, we introduced into Phoenix the support for Apache Omid - an open source transaction processor for HBase that is used at Yahoo at a large scale. A single Omid instance sustains hundreds of thousands of transactions per second, and provides high availability at zero cost for mainstream processing. Omid, as well as Tephra, are now configurable choices for the Phoenix transaction processing backend, being enabled by the newly introduced Transaction Abstraction Layer (TAL) API. In this talk, we walk through the challenges of the project, focusing on the new use cases introduced by Phoenix, and how we address them in Omid.">Omid - a Scalable and Highly Available Transaction Processing for Phoenix</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;">Ohad Shacham, Edward Bortnikov</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;"> Yahoo</TD>
</TR>
<TR STYLE="background-color: #f5f5f5;">
<TD STYLE="border: 1px solid #000000; padding: 5px;">5:15</TD>
<TD STYLE="border: 1px solid #000000; padding: 5px;" COLSPAN="3">Happy Hour + Roadmap Discussion</TD>
</TR>
</TBODY>
</TABLE>
 
To see abstract of talk, please hover over title.

Salesforce Rincon Cafe

Our {communityGuidelinesLink} describe the sort of content we prohibit on Eventbrite. If you suspect an event may be in violation, you can report it to us so we can investigate.

To report other categories of prohibited or illegal content, submit {link}

PhoenixCon 2017

More events from Apache Phoenix

Discover more events from Apache Phoenix, from Science & Tech to other experiences you might love.

Still looking for the right event?

Explore all events in San Francisco and filter by date, category, and more to find the perfect fit.

PhoenixCon 2017

More events from Apache Phoenix

Discover more events from Apache Phoenix, from Science & Tech to other experiences you might love.

More Science & Tech events

Browse more Science & Tech events with different dates, prices, and formats to find your next great experience.

Still looking for the right event?

Explore all events in San Francisco and filter by date, category, and more to find the perfect fit.