20 posts tagged with "Hive"

Introduction​

In our previous article published in October 2018, we use the TPC-DS benchmark to compare the performance of Hive-LLAP and SparkSQL 2.3.1 included in HDP 3.0.1 along with Hive 3.1.0 on MR3 0.4. In this article, we update the result by testing SparkSQL 2.3.2 included in HDP 3.1.4. As in the previous experiment, we use the TPC-DS benchmark.

Introduction​

In our previous article published in October 2018, we use the TPC-DS benchmark to compare the performance of Hive-LLAP in HDP 3.0.1 (as well as HDP 2.6.4) and Hive 3 on MR3 0.4. We have shown that Hive 3 on MR3 yields consistently higher throughput than Hive-LLAP in concurrency tests, but since then, the performance of Hive-LLAP has improved considerably for concurrent queries. Thus we are interested in the question of how Hive on MR3 compares with Hive-LLAP in the latest lease of HDP.

Introduction​

In our previous article, we use the TPC-DS benchmark to compare the performance of three SQL-on-Hadoop systems: Impala 2.12.0+cdh5.15.2+0, Presto 0.217, and Hive 3.1.1 on MR3 0.6. It uses sequential tests to draw the following conclusion:

• Impala runs faster than Hive on MR3 on short-running queries that take less than 10 seconds.
• For long-running queries, Hive on MR3 runs slightly faster than Impala.
• For most queries, Hive on MR3 runs faster than Presto, sometimes an order of magnitude faster.

Introduction​

Do you trust Hive? Do you trust Presto? Do you trust Impala? Do you trust your SQL system?

Introduction​

In our previous article, we use the TPC-DS benchmark to compare the performance of five SQL-on-Hadoop systems: Hive-LLAP, Presto, SparkSQL, Hive on Tez, and Hive on MR3. As it uses both sequential tests and concurrency tests across three separate clusters, we believe that the performance evaluation is thorough and comprehensive enough to closely reflect the current state in the SQL-on-Hadoop landscape.

Introduction​

We often ask questions on the performance of SQL-on-Hadoop systems:

• How fast is Hive-LLAP in comparison with Presto, SparkSQL, or Hive on Tez?
• As it is an MPP-style system, does Presto run the fastest if it successfully executes a query?
• As it stores intermediate data in memory, does SparkSQL run much faster than Hive on Tez in general?
• What is the best system for running concurrent queries?
• ...

NOTE: This article is superceded by a new article expanded with results of concurrency tests on newer versions of SQL-on-Hadoop systems.​

Introduction​

Hive running on top of MR3 0.2, or Hive-MR3 henceforth, supports LLAP (Low Latency Analytical Processing) I/O. In conjunction with the ability to execute multiple TaskAttempts concurrently inside a single ContainerWorker, the support for LLAP I/O makes Hive-MR3 functionally equivalent to Hive-LLAP. Hence Hive-MR3 can now serve as a substitute for Hive-LLAP in typical use cases.

Introduction​

In order to check if Hive running on top of MR3, or Hive-MR3 henceforth, is ready for production environments, we should test it for performance, stability, and scalability in multi-user environments in which many queries run concurrently. While Hive-on-Tez does a good job in multi-user environments, an analysis of the architecture of Tez reveals that we can further improve its support for multi-user environments by allowing a single DAGAppMaster to manage multiple concurrent DAGs. One of the design goals of MR3 is to overcome this limitation of Tez so as to better support multi-user environments as a new execution engine of Hive.

Introduction​

Since Hive running on top of MR3, or Hive-MR3 henceforth, uses MR3 as its execution engine and borrows runtime environments from Tez, a natural question arises as to whether the use of MR3 results in performance improvement in terms of execution time, turnaround time, or overall throughput at all. While it is difficult to accurately quantify the performance of MR3 over Tez as an execution engine, we can compare Hive-MR3 and Hive-on-Tez under identical conditions to see if there is any benefit of using MR3 in place of Tez.