_cardinality-estimation-through-histogram-in-apache-spark-2-3ron-hu-huawei-technologieszhenhua-wang-huawei-technologie.jpg "Cardinality Estimation through Histogram in Apache Spark 2.3Ron Hu (Huawei Technologies)Zhenhua Wang (Huawei Technologies) from change column length Video Screenshot Preview")
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⏲ Duration: 18 min 15 sec
✓ Published: 14-Jun-2018
✓ Published: 14-Jun-2018
Description:
Apache Spark 2.2 shipped with a state-of-art cost-based optimization framework that collects and leverages a variety of per-column data statistics (e.g., cardinality, number of distinct values, NULL values, max/min, avg/max length, etc.) to improve the quality of query execution plans. Skewed data distributions are often inherent in many real world applications. In order to deal with skewed distributions effectively, we added equal-height histograms to Apache Spark 2.3. Leveraging reliable stati
Apache Spark 2.2 shipped with a state-of-art cost-based optimization framework that collects and leverages a variety of per-column data statistics (e.g., cardinality, number of distinct values, NULL values, max/min, avg/max length, etc.) to improve the quality of query execution plans. Skewed data distributions are often inherent in many real world applications. In order to deal with skewed distributions effectively, we added equal-height histograms to Apache Spark 2.3. Leveraging reliable stati
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