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Amazon Redshift’s DISTKEY and SORTKEY are a powerful set of tools for optimizing query performance. In this series of articles, we will walk through a few interesting examples of how the DISTKEY and SORTKEY affects Redshift query performance.Amazon Redshift’s DISTKEY and SORTKEY are a powerful set of tools for optimizing query performance. Because Redshift is a columnar database with compressed storage, it doesn’t use indexes that way a transactional database such as MySQL or PostgreSQL would. Instead, it uses DISTKEYs and SORTKEYs.Choosing the values to use as your DISTKEcY and SORTKEY is not as straightforward as you might think. In fact, setting a DISTKEY/SORTKEY that is not well-thought-out can even worsen your query performance. In this series of articles, I’d like to show you a few interesting examples of how the Amazon Redshift DISTKEY and SORTKEY affects query performance.
Know Thy Data.In this example, I use a series of tables called systemerrors# where # is a series of numbers. Each record of the table consists of an error that happened on a system, with its (1) timestamp, and (2) error code. Each table has 282 million rows in it (lots of errors!). Here, I have a query which I want to optimize. The query gets the number of errors per error type, for each time slice. SELECT errcode, createdat, count(.) FROM systemerrors1 GROUP BY createdat, errcode;Before setting the DISTKEY, let’s without it, and see how the query performs.
CREATE TABLE systemerrors1 (errcode INTEGER,createdat timestamp);On my Redshift cluster (2-node dc1.large), the query took 20.52 seconds to execute. This isn’t too bad, considering the number of rows in the table. But if you look at the CPU usage, both compute nodes were used up to 30% of CPU. Let’s see how we can improve this by investigating our query performance.
Investigating The QueryLet’s check the query performance by checking the Amazon Redshift Console. Thankfully, it offers useful graphs and metrics to analyze query performance.
Below is what the “Query Execution Details” for the query looked like. Look at the warning sign! Something must have been wrong. Let’s see the details. This warning occurred because rows to be aggregated (rows sharing the same errcode and createdat values) are spread across multiple compute nodes. Windows 8 enterprise evaluation activation crack free. Each node must aggregate its own rows first; then the leader node has to aggregate the results again. That’s why you see two “Aggregate” steps in the above screenshot.
More importantly, a large amount data was sent to the leader node across the network, which became the performance bottleneck. We can avoid this by putting all rows sharing the same errcode and createdat values on a single node. This can be done by defining the DISTKEY. Adding DISTKEY and SORTKEYTo collocate all relevant rows in a single node, we can use either the column errcode or createdat as the DISTKEY. Since I also want to run a query grouped by errcode without createdat, I chose errcode as DISTKEY and SORTKEY. CREATE TABLE systemerrors2 (errcode INTEGER,createdat timestamp) DISTKEY(errcode) SORTKEY(errcode);Let’s see how the query performs against the new table.
SELECT errcode, createdat, count(.) FROM systemerrors2 GROUP BY createdat, errcode;Shockingly, this query took 54.9 seconds! That’s 2.5 times slower than the first query against a table with no DISTKEY/SORTKEY. This new table puts all rows of an error code on the same node and stores them next to each other. Why would the query against this table be even slower than the table with no DISTKEY/SORTKEY?? Solving The PuzzleWe created two tables with and without DISTKEY and found that the one with the DISTKEY was much slower than the other. No DISTKEY - 20.52 secondserrcode as DISTKEY - 54.9 secondsWhy did this happen?
Let’s check the query’s execution details. You’ll notice the long red lines. This means that the slowest node took significantly longer than the average processing time. In this case, it took 4 times more than the average. The slowest node must have had more rows than the other nodes.
Let’s run the following query and see how many rows each errcode has. SELECT errcode, count(.) FROM systemerrors2 GROUP BY errcode;errcode count-+-1210 8 38410009 1 6 3 896010006 07 678401204 209 281856(14 rows)You can see that one of the error codes (1204) has an extremely large number of rows compared to the others. It actually has 95.5% of the rows in the table. Because we used errcode as the DISTKEY, at least 95.5% of the rows were put on one particular node. This is the so-called skew. When such skew occurs, the total query processing time takes much longer because the performance is capped by the slowest processing node; i.e., the query cannot be spread across multiple nodes.
In this (extreme) case, almost all the rows were processed by a single node. That is why the query took longer than the query made against the table without a DISTKEY.
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Trying a Different DISTKEY and SORTKEYSince the values of the column errcode was too skewed to use as a DISTKEY, let’s use the other column createdat instead. CREATE TABLE systemerrors3 (errcode INTEGER,createdat timestamp) DISTKEY(createdat) SORTKEY(createdat);The same query now takes only 8.32 seconds to return, more than 6 times faster than the previous query, and more than twice as fast as our very first query. CPU Utilization is also much better; 10% vs the previous 30%. Query execution details look good as well. Skew is minimal, and also there is no warning sign for a large data transfer across the network. If you look at the details of Hash Aggregation, you will notice that the steps are much more simplified compared to our very first query.
The double “Aggregate” is no longer to be seen! Summary. Pick a few important queries you want to optimize your databases for. You can’t optimize your table for all queries, unfortunately. To avoid a large data transfer over the network, define a DISTKEY.
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From the columns used in your queries, choose a column that causes the least amount of skew as the DISTKEY. A column which has many distinct values, such as timestamp, would be a good first choice. Avoid columns with few distinct values, such as credit card types, or days of week.
Even though it will almost never be the best performer, a table with no DISTKEY/SORTKEY is a decent all-around performer. It’s a good option not to define DISTKEY and SORTKEY until you really understand the nature of your data and queries.How FlyData Helpsprovides continuous, real-time database replication to Amazon Redshift. It offers a reliable, powerful way to simplify your data analytics pipeline in a single interface without manual scripting.With a free 14-day trial, you can get your data synced in just minutes.
For questions about FlyData and how we can help accelerate your use-case and journey on Amazon Redshift, connect with us at.
In the of a of distant galaxies (right), as compared to absorption lines in the visible spectrum of the (left). Arrows indicate redshift. Wavelength increases up towards the red and beyond (frequency decreases).In, redshift is a phenomenon where (such as ) from an object undergoes an increase in. Whether or not the radiation is visible, 'redshift' means an increase in wavelength, equivalent to a decrease in wave and, in accordance with, respectively, the wave and theories of light.Neither the emitted nor perceived light is necessarily red; instead, the term refers to the human perception of longer wavelengths as, which is at the section of the with the longest wavelengths. Examples of redshifting are a perceived as an, or initially visible light perceived as. The opposite of a redshift is a, where wavelengths shorten and energy increases. However, redshift is a more common term and sometimes blueshift is referred to as negative redshift.There are three main causes of redshifts in astronomy and cosmology:.
Objects move apart (or closer together) in space. This is an example of the., causing objects to become separated without changing their positions in space. This is known as redshift. All sufficiently distant light sources (generally more than a few million away) show redshift corresponding to the rate of increase in their distance from Earth, known as. is a effect observed due to strong, which distort and exert a force on light and other particles.Knowledge of redshifts and blueshifts has been used to develop several terrestrial technologies such as.
Redshifts are also seen in the observations of objects. Its value is represented by the letter z.A (and its ) can be used to calculate the redshift of a nearby object when is. However, in many contexts, such as and cosmology, redshifts must be calculated using. Special relativistic, gravitational, and cosmological redshifts can be understood under the umbrella of. There exist other physical processes that can lead to a shift in the frequency of electromagnetic radiation, including and; however, the resulting changes are distinguishable from true redshift and are not generally referred to as such (see section on ). Plot of distance (in ) vs. Redshift according to the.
D H (in solid black) is the from Earth to the location with the Hubble redshift z while ct LB (in dotted red) is the speed of light multiplied by the lookback time to Hubble redshift z. The comoving distance is the physical distance between here and the distant location, to the at some 47 billion light-years. The lookback time is the distance a photon traveled from the time it was emitted to now divided by the speed of light, with a maximum distance of 13.8 billion light-years corresponding to the.Currently, the objects with the highest known redshifts are galaxies and the objects producing gamma ray bursts.
The most reliable redshifts are from data, and the highest-confirmed spectroscopic redshift of a galaxy is that of, with a redshift of z = 11.1, corresponding to 400 million years after the Big Bang. The previous record was held by at a redshift of z = 8.6, corresponding to 600 million years after the Big Bang. Slightly less reliable are redshifts, the highest of which is the lensed galaxy A1689-zD1 at a redshift z = 7.5 and the next highest being z = 7.0. The most distant-observed with a spectroscopic redshift measurement was, which had a redshift of z = 8.2. The most distant-known quasar, is at z = 7.54. The highest-known redshift radio galaxy (TN J0924-2201) is at a redshift z = 5.2 and the highest-known redshift molecular material is the detection of emission from the CO molecule from the quasar SDSS J1148+5251 at z = 6.42Extremely red objects (EROs) are of radiation that radiate energy in the red and near infrared part of the electromagnetic spectrum.
These may be starburst galaxies that have a high redshift accompanied by reddening from intervening dust, or they could be highly redshifted elliptical galaxies with an older (and therefore redder) stellar population. Objects that are even redder than EROs are termed hyper extremely red objects (HEROs).The has a redshift of z = 1089, corresponding to an age of approximately 379,000 years after the Big Bang and a of more than 46 billion light-years. The yet-to-be-observed first light from the oldest, not long after atoms first formed and the CMB ceased to be absorbed almost completely, may have redshifts in the range of 20 10 10) and the cosmic emitted directly from at a redshift in excess of z 10 25.In June 2015, astronomers reported evidence for in the at z = 6.60. Such stars are likely to have existed in the very early universe (i.e., at high redshift), and may have started the production of heavier than that are needed for the later formation of and as we know it. Redshift surveys. Main article:With advent of automated and improvements in, a number of collaborations have been made to map the universe in redshift space.
By combining redshift with angular position data, a redshift survey maps the 3D distribution of matter within a field of the sky. These observations are used to measure properties of the of the universe. The, a vast of galaxies over 500 million wide, provides a dramatic example of a large-scale structure that redshift surveys can detect.The first redshift survey was the, started in 1977 with the initial data collection completed in 1982. More recently, the determined the large-scale structure of one section of the universe, measuring redshifts for over 220,000 galaxies; data collection was completed in 2002, and the final was released 30 June 2003. The (SDSS), is ongoing as of 2013 and aims to measure the redshifts of around 3 million objects. SDSS has recorded redshifts for galaxies as high as 0.8, and has been involved in the detection of beyond z = 6.
The uses the with the new 'DEIMOS'; a follow-up to the pilot program DEEP1, DEEP2 is designed to measure faint galaxies with redshifts 0.7 and above, and it is therefore planned to provide a high-redshift complement to SDSS and 2dF. Effects from physical optics or radiative transfer The interactions and phenomena summarized in the subjects of and can result in shifts in the wavelength and frequency of electromagnetic radiation. In such cases, the shifts correspond to a physical energy transfer to matter or other photons rather than being by a transformation between reference frames. Such shifts can be from such physical phenomena as or the of whether from, from, or from fluctuations of the in a medium as occurs in the radio phenomenon of. While such phenomena are sometimes referred to as 'redshifts' and 'blueshifts', in astrophysics light-matter interactions that result in energy shifts in the radiation field are generally referred to as 'reddening' rather than 'redshifting' which, as a term, is normally reserved for the.In many circumstances scattering causes radiation to redden because results in the predominance of many low- photons over few high-energy ones (while ). Except possibly under carefully controlled conditions, scattering does not produce the same relative change in wavelength across the whole spectrum; that is, any calculated z is generally a of wavelength.
Furthermore, scattering from generally occurs at many, and z is a function of the scattering angle. If multiple scattering occurs, or the scattering particles have relative motion, then there is generally distortion of as well.In, can appear redder due to scattering processes in a phenomenon referred to as —similarly causes the reddening of the Sun seen in the sunrise or sunset and causes the rest of the sky to have a blue color. This phenomenon is distinct from red shifting because the lines are not shifted to other wavelengths in reddened objects and there is an additional and distortion associated with the phenomenon due to photons being scattered in and out of the.For a list of scattering processes, see. References.