In fast action ad-hoc queries, Hive LLAP’s start-up times may slow it down compared with Impala, yet with longer running queries, this start-up cost is a relatively inconsequential part of the total run time. Most Users Ever Online: 107. Forum Timezone: Australia/Brisbane. kill-long-running-impala-queries. Hive LLAP becomes a better choice for EDW also because of its fault tolerance (who wants a query to fail if you are waiting a long time for the result?) 2,260 Views 0 Kudos 1 REPLY 1. minutes), the profile timers are not updated to reflect the time spent in the sort until the sort starts returning rows. SELECT query_duration from IMPALA_QUERIES WHERE service_name = "REPLACE-WITH-IMPALA-SERVICE-NAME" AND query_type = "DDL" **Max value for Y range in DDL Run time defaults to 100ms, make sure it’s unset. ## Kills Long Running Impala Queries ## ## Usage: ./killLongRunningImpalaQueries.py queryRunningSeconds [KILL] ## ## Set queryRunningSeconds to the threshold considered "too long" ## for an Impala query to run, so that queries that have been running ## longer than that will be identifed as queries to be killed ## The HPE Ezmeral DF Support Portal provides customers and big data enthusiasts access to hundreds of self-service knowledge articles crafted from known issues, answers to the most common questions we receive from customers, past issue resolutions, and alike. Pretty printing is quite slow. Also, it can be integrated with HBASE or Amazon S3. Now I get a lot of 'out of memory' Exceptions when I run queries. In the future, we foresee it can reduce disk utilization by over 20% for our planned elastic computing on Impala. Sometime, I have queries that are supposed to take only few seconds keeping running and running, and blocking other queries, or queries tweaked with a value set to MT_DOP too big which put impala on their knees.. In our project “Beacon Growing”, we have deployed Alluxio to improve Impala performance by 2.44x for IO intensive queries and 1.20x for all queries. this is a summary from a sort query that was running for a few hours . The Impala administrator cannot be relied upon to know which node the user connected to when submitting the query and some people may also put load balancers in front of the entire Impala cluster. You can use the Hive Query executor with any event-generating stage where the logic suits your needs. You can make use of the –var=variable_name option in the impala … E.g. Create a date-limited view on a hive table containing complex types in a way that is queryable with Impala? If there is an I/O problem with storage devices, or with HDFS itself, Impala queries could show slow response times with no obvious cause on the Impala side. Reply. A BDA cluster exhibits increased query times and slow performance when running hive and Impala jobs. CDH 4.3, impala 1.0.1, CM 4.6, can't kill impala queries using CM activities tab. For example, some jobs that normally take 5 minutes are taking more than one hour. If there is an I/O problem with storage devices, or with HDFS itself, Impala queries could show slow response times with no obvious cause on the Impala side. I hope you realize that the information you've provided is not enough to understand why the refresh takes a long time. Impala data is … The following sections describe known issues and workarounds in Impala, as of the current production release. Reply. Cloudera Manager's Impala Queries page allows Impala queries to be monitored, managed and cancelled (killed) as desired: This script provides an example of using Cloudera Manager's Python API Client to programmatically list and/or kill Impala queries that have been running longer than a user-defined threshold. If the cluster is relatively busy and your workload contains many resource-intensive or long-running queries, consider increasing the wait time so that complicated queries do not miss opportunities for optimization. How to use Impala query plan and profile to fix performance issues Juan Yu Impala Field Engineer, Cloudera . The refresh time is strictly related to what your query does, and the measures you wrote. For example, one query failed to compile due to missing rollup support within Impala. Impala partition queries running slow. The trick however is in finding the query planner node controlling the query. By executing these queries, we can see massive time difference between Hive and Impala when executing low latency queries. Failed to get minimum memory reservation of 3.94 MB on daemon r5c3s4.colo.vm:22000 for query 924d155863398f6b:c4a3470300000000 because it would exceed an applicable memory limit. Profiles?! Deep knowledge about how to rewrite SQL statements was required to ensure a head-to-head comparison across non-Impala systems to avoid even slower response times and outright query failures, in some cases. It can be used to share the database of the hive as it can connect hive metastore easily. If the memory pressure is due to running many concurrent queries rather than a few memory-intensive ones, consider using the Impala admission control feature to lower the limit on the number of concurrent queries. It offers a high degree of compatibility with the Hive Query Language (HiveQL). Our query completed in 930ms .Here’s the first section of the query profile from our example and where we’ll focus for our small queries. The Hive Query executor is designed to run a set of Hive or Impala queries after receiving an event record. In addition, we will also discuss Impala Data-types. Now I get a lot of 'out of memory' Exceptions when I run queries. Activity. If the refresh time is slow, then the query is slow. Cloudera Manager's Impala Queries page allows Impala queries to be monitored, managed and cancelled (killed) as desired: This script provides an example of using Cloudera Manager's Python API Client to programmatically list and/or kill Impala queries that have been running longer than a user-defined threshold. The reason that partitions are so important is that they can help dramatically narrow down the amount of data that Impala has to read when running a query. kill-long-running-impala-queries. Therefore, the pass-through query may be executed at various times to retrieve information related to its definition. 9:19. Additionally, this is the primary interface for HPE Ezmeral DF customers to engage our support team, manage open cases, validate … In this case, admission control improves the reliability and stability of the overall workload by only allowing as many concurrent queries as the overall memory of the cluster can accommodate. The other systems required significant rewrites of the original queries in order to run, while Impala could run the original as well as modified queries. Impala is developed by Cloudera distribution to overcome the slow processing of hive queries. However, there is much more to learn about Impala SQL, which we will explore, here. Hot Network Questions Category theory and arithmetical identities How were the cities of Milan and Bruges spared by the Black Death? If you have a query plan with a long-running sort operation (e.g. People. The query failure rate due to timeout is also reduced by 29%. Thanks. Validate Impala by running Commands and Queries - Duration: 9:19. itversity 243 views. Planning Wait Time: 18.8m Planning Wait Time Percentage: 100 . Virtual machine is running on server grid. Because Impala by default cancels queries that exceed the specified memory limit, running multiple large-scale queries at once might require re-running some queries that are cancelled. What is the reason for the date of the Georgia runoff elections for the US Senate? If TotalRawHdfsReadTime is high, reading from the storage system may be slow (e.g. 1. Impala works better in comparison to a hive when a dataset is not huge. I am running a Query which returns 5 rows select distinct date_key from tbl_date limit 5; /the table has a few hundred rows with 1 partition/. Highlighted. if the data is not in the OS buffer cache or it is a remote filesystem like S3) Other queries may be contending for I/O resources and/or I/O threads The summary was misleading and the "heat map" plan in the debug web UI is misleading - it showed the join as the "hot" operator. Impala queries are typically I/O-intensive. In this Impala SQL Tutorial, we are going to study Impala Query Language Basics. Created ‎01-16-2017 08:08 AM. Impala was designed to be highly compatible with Hive, but since perfect SQL parity is never possible, 5 queries did not run in Impala due to syntax errors. This page summarizes the most serious or frequently encountered issues in the current release, to help you make planning decisions about installing and upgrading. It may have been possible to find Impala-specific workarounds to these gaps, but no attempt was made to do so since these results could not be … For example, running a query from impala-shell with and w/o -B makes the query run in 14.5s and 2.5s respectively. Re: Hive Queries run slowly MasterOfPuppets. Impala queries are typically I/O-intensive. As one might wonder why DML waits for a metadata update … Objective – Impala Query Language. But pls be aware that impala will use more memory. Arggghh… § For the end user, understanding Impala performance is like… - Lots of commonality between requests, e.g. CDH 5.7/Impala shell version 2.5 and higher run Impala SQL Script File Passing argument. Cause. Impala took less than a second to select 2 rows whereas; Hive took 29.57 seconds to fetch 2 records. Explain plans!? Attachments. 1. Still if you need quick result, you have to login to impala-shell instead of Hive and run your query. The Query info is . When the pass-through query takes considerable time to execute, Access … Contributor. See Why Impala spend a lot of time Opening HDFS File (TotalRawHdfsOpenFileTime)? Impala 1.3.1 join query crash impala daemons; Impala - running queries in parallel issue; Impala 1.2.1 query scalability question; Query Throughput; Re: Support for windowing functions in Impala. Below are part of the profile for the two runs – run impala-shell (pretty-printing) ExecSummary: Operator #Hosts Avg Time Max Time #Rows Est. A query profile can be obtained after running a query in many ways by: issuing a PROFILE; statement from impala-shell, through the Impala Web UI, via HUE, or through Cloudera Manager. How to set Impala query options: ... to guard against the possibility of a single slow host taking too long. We were running queries (with mem limits set in Impala) like the following one after another (only one query was executing at the same time at any point). Note: The planning wait time is for searching and finding DML commands that are waiting for a metadata update. In this cluster, users typically access both applications via the web UI in Oozie and hue, but slow performance is also seen with the client applications. Can we check the detailed logging of impala queries apart from the Impala query UI, to get an idea why things are slowing down? On running the above query, Impala took only 0.95 seconds. By spacing out the most resource-intensive queries, you can avoid spikes in memory usage and improve overall response times. 20,165 Views 0 Kudos Highlighted. I'm running a cluster of 5 Impala-Nodes for my Api. #Rows Peak Mem Est. Microsoft Access does not store the definition for a pass-through query. 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