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| <div class="collapse" id="collapse_background"> |
| <li><a href="/docs/Background/TheChallenge.html">•The Challenge</a></li> |
| <li><a href="/docs/Background/SketchOrigins.html">•Sketch Origins</a></li> |
| <li><a href="/docs/Background/SketchElements.html">•Sketch Elements</a></li> |
| <li><a href="/docs/Background/Presentations.html">•Presentations</a></li> |
| <li><a href="https://github.com/apache/datasketches-website/tree/master/docs/pdf/DataSketches_deck.pdf">•Overview Slide Deck</a></li> |
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| <li><a href="/docs/Architecture/MajorSketchFamilies.html">•The Major Sketch Families</a></li> |
| <li><a href="/docs/Architecture/LargeScale.html">•Large Scale Computing</a></li> |
| <li><a href="/docs/Architecture/KeyFeatures.html">•Key Features</a></li> |
| <li><a href="/docs/Architecture/SketchFeaturesMatrix.html">•Sketch Features Matrix</a></li> |
| <li><a href="/docs/Architecture/Components.html">•Components</a></li> |
| <li><a href="/docs/Architecture/SketchesByComponent.html">•Sketches by Component</a></li> |
| <li><a href="/docs/Architecture/SketchCriteria.html">•Sketch Criteria</a></li> |
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| <p id="memory-component"> |
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| <li><a href="/docs/Memory/MemoryComponent.html">•Memory Component</a></li> |
| <li><a href="/docs/Memory/MemoryPerformance.html">•Memory Component Performance</a></li> |
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| <li><a href="/docs/Architecture/OrderSensitivity.html">•Notes on Order Sensitivity</a></li> |
| <li><a href="/docs/Architecture/Concurrency.html">•Notes on Concurrency</a></li> |
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| <li><a href="/docs/DistinctCountFeaturesMatrix.html">•Features Matrix</a></li> |
| <li><a href="/docs/DistinctCountMeritComparisons.html">•Figures-of-Merit Comparison</a></li> |
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| <p id="cpc-sketches"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_cpc_sketches">CPC Sketches</a> |
| </p> |
| <div class="collapse" id="collapse_cpc_sketches"> |
| <li><a href="/docs/CPC/CPC.html">•CPC Sketch</a></li> |
| <li><a href="/docs/CPC/CpcPerformance.html">•CPC Sketch Performance</a></li> |
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| <a data-toggle="collapse" class="menu collapsed" href="#collapse_cpc_examples">CPC Examples</a> |
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| <li><a href="/docs/CPC/CpcJavaExample.html">•CPC Sketch Java Example</a></li> |
| <li><a href="/docs/CPC/CpcCppExample.html">•CPC Sketch C++ Example</a></li> |
| <li><a href="/docs/CPC/CpcPigExample.html">•CPC Sketch Pig UDFs</a></li> |
| <li><a href="/docs/CPC/CpcHiveExample.html">•CPC Sketch Hive UDFs</a></li> |
| </div> |
| </div> |
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| <p id="hyperloglog-sketches"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_hyperloglog_sketches">HyperLogLog Sketches</a> |
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| <li><a href="/docs/HLL/HLL.html">•HLL Sketch</a></li> |
| <li><a href="/docs/HLL/HllMap.html">•HLL Map Sketch</a></li> |
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| <p id="hll-examples"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_hll_examples">HLL Examples</a> |
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| <li><a href="/docs/HLL/HllJavaExample.html">•HLL Sketch Java Example</a></li> |
| <li><a href="/docs/HLL/HllCppExample.html">•HLL Sketch C++ Example</a></li> |
| <li><a href="/docs/HLL/HllPigUDFs.html">•HLL Sketch Pig UDFs</a></li> |
| <li><a href="/docs/HLL/HllHiveUDFs.html">•HLL Sketch Hive UDFs</a></li> |
| </div> |
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| <p id="hll-studies"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_hll_studies">HLL Studies</a> |
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| <div class="collapse" id="collapse_hll_studies"> |
| <li><a href="/docs/HLL/HllPerformance.html">•HLL Sketch Performance</a></li> |
| <li><a href="/docs/HLL/Hll_vs_CS_Hllpp.html">•HLL vs Clearspring HLL++</a></li> |
| <li><a href="/docs/HLL/HllSketchVsDruidHyperLogLogCollector.html">•HLL Sketch vs Druid HyperLogLogCollector</a></li> |
| </div> |
| </div> |
| |
| <p id="theta-sketches"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_theta_sketches">Theta Sketches</a> |
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| <div class="collapse" id="collapse_theta_sketches"> |
| <li><a href="/docs/Theta/ThetaSketchFramework.html">•Theta Sketch Framework</a></li> |
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| <p id="theta-examples"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_theta_examples">Theta Examples</a> |
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| <div class="collapse" id="collapse_theta_examples"> |
| <li><a href="/docs/Theta/ConcurrentThetaSketch.html">•Concurrent Theta Sketch</a></li> |
| <li><a href="/docs/Theta/ThetaJavaExample.html">•Theta Sketch Java Example</a></li> |
| <li><a href="/docs/Theta/ThetaSparkExample.html">•Theta Sketch Spark Example</a></li> |
| <li><a href="/docs/Theta/ThetaPigUDFs.html">•Theta Sketch Pig UDFs</a></li> |
| <li><a href="/docs/Theta/ThetaHiveUDFs.html">•Theta Sketch Hive UDFs</a></li> |
| </div> |
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| <p id="kmv-tutorial"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_kmv_tutorial">KMV Tutorial</a> |
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| <div class="collapse" id="collapse_kmv_tutorial"> |
| <li><a href="/docs/Theta/InverseEstimate.html">•The Inverse Estimate</a></li> |
| <li><a href="/docs/Theta/KMVempty.html">•Empty Sketch</a></li> |
| <li><a href="/docs/Theta/KMVfirstEst.html">•First Estimator</a></li> |
| <li><a href="/docs/Theta/KMVbetterEst.html">•Better Estimator</a></li> |
| <li><a href="/docs/Theta/KMVrejection.html">•Rejection Rules</a></li> |
| <li><a href="/docs/Theta/KMVupdateVkth.html">•Update V(kth) Rule</a></li> |
| </div> |
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| <p id="set-operations-and-p-sampling"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_set_operations_and_p-sampling">Set Operations and P-sampling</a> |
| </p> |
| <div class="collapse" id="collapse_set_operations_and_p-sampling"> |
| <li><a href="/docs/Theta/ThetaSketchSetOps.html">•Set Operations</a></li> |
| <li><a href="/docs/Theta/ThetaSetOpsCornerCases.html">•Model & Test Set Operations</a></li> |
| <li><a href="/docs/Theta/ThetaPSampling.html">•<i>p</i>-Sampling</a></li> |
| </div> |
| |
| <p id="accuracy"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_accuracy">Accuracy</a> |
| </p> |
| <div class="collapse" id="collapse_accuracy"> |
| <li><a href="/docs/Theta/ThetaAccuracy.html">•Basic Accuracy</a></li> |
| <li><a href="/docs/Theta/ThetaAccuracyPlots.html">•Accuracy Plots</a></li> |
| <li><a href="/docs/Theta/ThetaErrorTable.html">•Relative Error Table</a></li> |
| <li><a href="/docs/Theta/ThetaSketchSetOpsAccuracy.html">•SetOp Accuracy</a></li> |
| <li><a href="/docs/Theta/AccuracyOfDifferentKUnions.html">•Unions With Different k</a></li> |
| </div> |
| |
| <p id="size"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_size">Size</a> |
| </p> |
| <div class="collapse" id="collapse_size"> |
| <li><a href="/docs/Theta/ThetaSize.html">•Theta Sketch Size</a></li> |
| </div> |
| |
| <p id="speed"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_speed">Speed</a> |
| </p> |
| <div class="collapse" id="collapse_speed"> |
| <li><a href="/docs/Theta/ThetaUpdateSpeed.html">•Update Speed</a></li> |
| <li><a href="/docs/Theta/ThetaMergeSpeed.html">•Merge Speed</a></li> |
| </div> |
| |
| <p id="theta-sketch-theory"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_theta_sketch_theory">Theta Sketch Theory</a> |
| </p> |
| <div class="collapse" id="collapse_theta_sketch_theory"> |
| <li><a href="https://github.com/apache/datasketches-website/tree/master/docs/pdf/ThetaSketchFramework.pdf">•Theta Sketch Framework (PDF)</a></li> |
| <li><a href="https://github.com/apache/datasketches-website/tree/master/docs/pdf/ThetaSketchEquations.pdf">•Theta Sketch Equations (PDF)</a></li> |
| <li><a href="https://github.com/apache/datasketches-website/tree/master/docs/pdf/DataSketches.pdf">•DataSketches (PDF)</a></li> |
| <li><a href="/docs/Theta/ThetaConfidenceIntervals.html">•Confidence Intervals Notes</a></li> |
| <li><a href="/docs/Theta/ThetaMergingAlgorithm.html">•Merging Algorithm Notes</a></li> |
| <li><a href="/docs/Theta/ThetaReferences.html">•Theta References</a></li> |
| </div> |
| </div> |
| |
| <p id="tuple-sketches"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_tuple_sketches">Tuple Sketches</a> |
| </p> |
| <div class="collapse" id="collapse_tuple_sketches"> |
| <li><a href="/docs/Tuple/TupleOverview.html">•Tuple Overview</a></li> |
| |
| <p id="tuple-examples"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_tuple_examples">Tuple Examples</a> |
| </p> |
| <div class="collapse" id="collapse_tuple_examples"> |
| <li><a href="/docs/Tuple/TupleJavaExample.html">•Tuple Java Example</a></li> |
| <li><a href="/docs/Tuple/TupleEngagementExample.html">•Tuple Engagement Example</a></li> |
| <li><a href="/docs/Tuple/TuplePigUDFs.html">•Tuple Pig UDFs</a></li> |
| <li><a href="/docs/Tuple/TupleHiveUDFs.html">•Tuple Hive UDFs</a></li> |
| </div> |
| </div> |
| </div> |
| |
| <p id="most-frequent"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_most_frequent">Most Frequent</a> |
| </p> |
| <div class="collapse" id="collapse_most_frequent"> |
| <li><a href="/docs/Frequency/FrequencySketchesOverview.html">•Frequency Sketches Overview</a></li> |
| |
| <p id="frequent-item-sketches"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_frequent_item_sketches">Frequent Item Sketches</a> |
| </p> |
| <div class="collapse" id="collapse_frequent_item_sketches"> |
| <li><a href="/docs/Frequency/FrequentItemsOverview.html">•Frequent Items Overview</a></li> |
| <li><a href="/docs/Frequency/FrequentItemsErrorTable.html">•Frequent Items Error Table</a></li> |
| <li><a href="/docs/Frequency/FrequentItemsReferences.html">•Frequent Items References</a></li> |
| <li><a href="/docs/Frequency/FrequentItemsPerformance.html">•Frequent Items Performance</a></li> |
| |
| <p id="most-frequent-examples"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_most_frequent_examples">Most Frequent Examples</a> |
| </p> |
| <div class="collapse" id="collapse_most_frequent_examples"> |
| <li><a href="/docs/Frequency/FrequentItemsJavaExample.html">•Frequent Items Java Example</a></li> |
| <li><a href="/docs/Frequency/FrequentItemsCppExample.html">•Frequent Items C++ Example</a></li> |
| <li><a href="/docs/Frequency/FrequentItemsPigUDFs.html">•Frequent Items Pig UDFs</a></li> |
| <li><a href="/docs/Frequency/FrequentItemsHiveUDFs.html">•Frequent Items Hive UDFs</a></li> |
| </div> |
| </div> |
| |
| <p id="frequent-distinct-sketches"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_frequent_distinct_sketches">Frequent Distinct Sketches</a> |
| </p> |
| <div class="collapse" id="collapse_frequent_distinct_sketches"> |
| <li><a href="/docs/Frequency/FrequentDistinctTuplesSketch.html">•Frequent Distinct Tuples Sketch</a></li> |
| </div> |
| </div> |
| |
| <p id="quantiles-and-histograms"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_quantiles_and_histograms">Quantiles And Histograms</a> |
| </p> |
| <div class="collapse" id="collapse_quantiles_and_histograms"> |
| <li><a href="/docs/Quantiles/SketchingQuantilesAndRanksTutorial.html">•Quantiles and Ranks Tutorial</a></li> |
| <li><a href="/docs/Quantiles/QuantilesOverview.html">•Quantiles Overview</a></li> |
| <li><a href="/docs/KLL/KLLSketch.html">•KLL Floats sketch</a></li> |
| <li><a href="/docs/KLL/KLLAccuracyAndSize.html">•KLL Sketch Accuracy and Size</a></li> |
| <li><a href="/docs/REQ/ReqSketch.html">•REQ Floats sketch</a></li> |
| <li><a href="/docs/Quantiles/OrigQuantilesSketch.html">•Original QuantilesSketch</a></li> |
| |
| <p id="quantiles-examples"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_quantiles_examples">Quantiles Examples</a> |
| </p> |
| <div class="collapse" id="collapse_quantiles_examples"> |
| <li><a href="/docs/Quantiles/QuantilesJavaExample.html">•Quantiles Sketch Java Example</a></li> |
| <li><a href="/docs/KLL/KLLCppExample.html">•KLL Quantiles Sketch C++ Example</a></li> |
| <li><a href="/docs/Quantiles/QuantilesPigUDFs.html">•Quantiles Sketch Pig UDFs</a></li> |
| <li><a href="/docs/Quantiles/QuantilesHiveUDFs.html">•Quantiles Sketch Hive UDFs</a></li> |
| </div> |
| |
| <p id="quantiles-studies"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_quantiles_studies">Quantiles Studies</a> |
| </p> |
| <div class="collapse" id="collapse_quantiles_studies"> |
| <li><a href="/docs/QuantilesStudies/DruidApproxHistogramStudy.html">•Druid Approximate Histogram</a></li> |
| <li><a href="/docs/QuantilesStudies/MomentsSketchStudy.html">•Moments Sketch Study</a></li> |
| <li><a href="/docs/QuantilesStudies/QuantilesStreamAStudy.html">•Quantiles StreamA Study</a></li> |
| <li><a href="/docs/QuantilesStudies/ExactQuantiles.html">•Exact Quantiles for Studies</a></li> |
| </div> |
| |
| <p id="quantiles-sketch-theory"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_quantiles_sketch_theory">Quantiles Sketch Theory</a> |
| </p> |
| <div class="collapse" id="collapse_quantiles_sketch_theory"> |
| <li><a href="https://github.com/apache/datasketches-website/tree/master/docs/pdf/Quantiles_KLL.pdf">•Optimal Quantile Approximation in Streams</a></li> |
| <li><a href="/docs/Quantiles/QuantilesReferences.html">•Quantiles References</a></li> |
| </div> |
| </div> |
| |
| <p id="sampling"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_sampling">Sampling</a> |
| </p> |
| <div class="collapse" id="collapse_sampling"> |
| <li><a href="/docs/Sampling/ReservoirSampling.html">•Reservoir Sampling</a></li> |
| <li><a href="/docs/Sampling/ReservoirSamplingPerformance.html">•Reservoir Sampling Performance</a></li> |
| <li><a href="/docs/Sampling/VarOptSampling.html">•VarOpt Sampling</a></li> |
| |
| <p id="sampling-examples"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_sampling_examples">Sampling Examples</a> |
| </p> |
| <div class="collapse" id="collapse_sampling_examples"> |
| <li><a href="/docs/Sampling/ReservoirSamplingJava.html">•Reservoir Sampling Java Example</a></li> |
| <li><a href="/docs/Sampling/ReservoirSamplingPigUDFs.html">•Reservoir Sampling Pig UDFs</a></li> |
| <li><a href="/docs/Sampling/VarOptSamplingJava.html">•VarOpt Sampling Java Example</a></li> |
| <li><a href="/docs/Sampling/VarOptPigUDFs.html">•VarOpt Sampling Pig UDFs</a></li> |
| </div> |
| </div> |
| </div> |
| |
| <p id="system-integrations"> |
| <a data-toggle="collapse" class="menu collapsed" href="#collapse_system_integrations">System Integrations</a> |
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| <h2 id="up-front--p-sampling">Up-Front / p Sampling</h2> |
| |
| <p>The up-front / p-sampling option of the Theta Sketches exists to address the system-level storage allocation challenge when dealing with highly partitioned/fragmented massive data that inherently has a long-tail distribution across all the fragments.</p> |
| |
| <p>Partitioning of Big Data into a large number of fragments will often reveal that the incoming data has a long tail (or, more precisely, a power-law distribution).</p> |
| |
| <p>For example, Yahoo has a few thousand “properties” and millions of Page-IDs/space-IDs, and users come from many thousands of Where-on-Earth geolocations across the globe. If you were to create a sketch for every dimension-combination of (Page-ID, WOE) you would end up with billions of fragments, each with its own sketch.</p> |
| |
| <p>As you might expect, you will have a few of those combinations, e.g. (Front-page, New York City) that have very large counts of unique users, and millions of combinations (some small web-app, some small town) that would have only one or 2 users. |
| The sketch automatically limits the number of hashes it keeps for the big combinations to k, while all the hashes are retained for the millions of tiny combinations. |
| When you examine the storage of all those sketches you will discover that roughly 80% of all the storage is consumed by the “degenerate sketches”, which are not sketching at all because they have not received more than k users.</p> |
| |
| <p>Setting the sampling to, say, p = 0.5, for all sketches, will automatically throw out 50% of all the data coming in to all the sketches. |
| A query against (FP, NYC) will have the same accuracy, with or without the p-sampling, because there is more than enough raw data to fill that sketch. |
| For all the tiny sketches, about half of the ones with only one user hash will disappear. |
| All of the degenerate sketches will be half of their original size when stored. |
| The effect of this is to reduce the overall system-level storage for all sketches by roughly 50%. |
| However, a query against (some small web-app, some small town) may return 0 because it has been “sampled” out. |
| It’s relative error is now infinity! Sketches with more than 1 sample and less the k samples will have error rates that are in-between, but still can be larger than the native RSE of the basic sketch. |
| This effect is illustrated in the following plot, which was created with p=0.5.</p> |
| |
| <p><img class="doc-img-half" src="/docs/img/theta/pSamplingPitchfork.png" alt="pSamplingPitchfork" /></p> |
| |
| <h3 id="the-p-sampling-error-behavior">The p-Sampling Error Behavior</h3> |
| |
| <p>At about 8K uniques there is an inflection point where the error changes direction and begins to increase rather than go toward zero as with the normal pitchfork plots. |
| To the right of this inflection point the error behavior is the same as a normal sketch, with p=1.0, which is the default. |
| To the left of this inflection point the error begins to increase.</p> |
| |
| <p>The inflection point is the result of two different error behaviors intersecting. |
| To the left of the inflection point the error behavior is that of standard Bernoulli sampling with a fixed probability equal to <i>p</i>. |
| To the right of the inflection point the error behavior is that of the underlying sketch.</p> |
| |
| <p>The following log-log plot illustrates these intersecting error behaviors more clearly.</p> |
| |
| <p><img class="doc-img-half" src="/docs/img/theta/RSE_4K_0p5.png" alt="RSE_4K_0p5" /></p> |
| |
| <p>The RSE (normalized square-root of the variance) of a Bernoulli sampling process, with fixed <i>p</i>, is a straight line on a log-log plot (plotted in blue). |
| The y intercept at x=1 is simply <i>(1/p -1)</i> and the log-log slope is -1/2. For p=0.5, the y intercept is 1.0 or 100% relative error. |
| So a sketch with only one retained hash value could return estimates of 0, 1 or 2. |
| Although the relative error is large, the absolute error is only +/- 1, which may not be significant.</p> |
| |
| <p>The green curve represents the theoretical RSE of the sketching process. |
| The red “X” markers are the measured RSE of the combined Bernoulli sampling process and the sketch process.</p> |
| |
| <h3 id="understanding-upper-and-lower-bounds-behavior-for-small-sketches-and-p-sampling">Understanding Upper and Lower Bounds Behavior For Small Sketches and p-Sampling</h3> |
| |
| <p>For p-sampling sketches with very small number of samples the error distribution is very complex and no longer can be modeled with the Gaussian distribution. |
| In order to provide the library user with meaningful getUpperBound() and getLowerBound() values at these very low sample sizes, |
| the library implements more sophisticated error models as illustrated in the following graph.</p> |
| |
| <p><img class="doc-img-half" src="/docs/img/theta/FractTrialsLB_0p5.png" alt="FractTrialsLB_0p5" /></p> |
| |
| <p>Each point along the X-axis is the result of 4096 trials. The fraction of those 4096 trials that are less than getLowerBound(1) (Purple) should be less than ~16%. |
| The scatter or variance is due to the quantization effects of only 4096 trials. The important thing to note is that for the very low count values, the purple markers |
| are all below the purple dashed line. Similarly, for getLowerBound(2) (Green), the markers should be less than ~2.3%. |
| The graph for the getUpperBound() values is very similar.</p> |
| |
| <p>As a result of this modeling, the upper and lower bounds values for these very small sample sizes are intentionally conservative. |
| If these bounds had been modeled assuming a Gaussian, the returned values would be way off.</p> |
| |
| <h3 id="summary">Summary</h3> |
| <p>The option of p-sampling provides the systems engineer and product manager with another “knob-to-turn” in trading off overall system storage and acceptable accuracy for small queries. |
| It is quite likely that for the majority of queries, which tend to be against the larger dimension-combinations, the error is quite acceptable. |
| And the product manager may decide that below some threshold size, the small queries have little business value, thus larger error on those queries may be acceptable.</p> |
| |
| <p>Using this capability must be a carefully thought-through business decision, which is also the case for any form of data sampling.</p> |
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