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new 39b92340 [DOCS] Create release notes for 3.1.0
39b92340 is described below
commit 39b9234078bc7703a8afe3063ef1ffa958b4e37a
Author: Janardhan Pulivarthi <[email protected]>
AuthorDate: Thu Mar 16 17:03:07 2023 +0000
[DOCS] Create release notes for 3.1.0
cbdae4046af0815df58eae36c22aa88034a16537
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+ <h2 id="release-notes-for-systemds-310">Release notes for SystemDS
3.1.0</h2>
+
+ <p>SystemDS 3.1 is a minor release. Release 3.1 contains new features
and major improvements to existing features.</p>
+
+ <h3 id="features-and-improvements">Features and Improvements</h3>
+
+ <ul>
+ <li>Performance codegen kmeans mnist80m w/ compression</li>
+ <li>Prefetch instruction</li>
+ <li>Broadcast instruction</li>
+ <li>Create apply functions for cleaning primitives</li>
+ <li>LogicalEnumerator change with transitions concept and cleanups</li>
+ <li>Flatten the nested loop for parallel pipelines execution</li>
+ <li>Adding apply_pipeline() builtin for cleaning pipelines API</li>
+ <li>Release docker images with GitHub actions</li>
+ <li>Add monitoring tool testing workflows</li>
+ <li>Asynchronous Execution and Persist Spark Transformations</li>
+ <li>Future-based asynchronous execution of Spark actions</li>
+ <li>New operator linearization order to maximize inter-operator
parallelism</li>
+ <li>Lineage-based reuse of Spark actions</li>
+ <li>Push down rmvar instructions for asynchronous instructions</li>
+ <li>Lineage-based reuse of asynchronous operators</li>
+ <li>Persist and reuse Spark RDDs</li>
+ <li>Refactor to add LOP rewrite step in compilation</li>
+ <li>Federated Compression Instruction</li>
+ <li>CLA IO Compressed Matrices</li>
+ <li>Compressed Max/Min Index support.</li>
+ <li>Federated async compression</li>
+ <li>Federated Workload-aware Compression</li>
+ <li>Python 3.9 support</li>
+ <li>Parallel Compressed Encode</li>
+ <li>New builtin function auc (area under ROC curve)</li>
+ <li>Unique() function for performance</li>
+ </ul>
+
+ <h3 id="bug">Bug</h3>
+
+ <ul>
+ <li>Fix memory configuration in sparkDML.sh</li>
+ <li>OOM Error On Binary Write</li>
+ <li>Out of memory error</li>
+ <li>CLA Improved Run estimation</li>
+ <li>AttributeError: Function definition not found</li>
+ <li>applySchema built-in to set the schema of frame from DML</li>
+ <li>CSR TSMM left with filled rows bug</li>
+ <li>Sparse TSMM dense row blocks CSR</li>
+ <li>py4j.Py4JException: Method exceptionString([class
org.apache.spark.SparkConf]) does not exist</li>
+ <li>MatrixBlock size using CSR when allowed</li>
+ <li>Federated Nan Values</li>
+ <li>countDistinctApprox() operation in AggregateUnaryCPInstruction is
inefficient for row/col aggregations</li>
+ <li>Correct the release artifact generation date</li>
+ <li>Log4j incompatible dependencies</li>
+ <li>ConcurrentModificationException in federated execution</li>
+ <li>Jackson Core missing for json writing and reading in reduced
binary</li>
+ <li>Fix Java doc warnings</li>
+ <li>Enque output not UTF-8 python</li>
+ <li>Read CSV directly without mtd python</li>
+ <li>Python configuration not loading defaults</li>
+ <li>Matrix Multiplication crash in Spark</li>
+ <li>Pipelines failing in Hybrid execution</li>
+ <li>Built-in tests failure in Git actions</li>
+ <li>Cleaning Pipelines failed with No space left on device</li>
+ <li>IndexOutOfBounds due to int overflow on replace</li>
+ <li>Cleaning Pipelines: Replace function failure in hybrid
execution</li>
+ <li>Cleaning Pipelines: Block Sizes mismatch</li>
+ <li>Cleaning Pipelines in hybrid mode: Invalid block dimensions
error</li>
+ <li>Federated Statistics print in non federated scenario</li>
+ <li>Spark Aggregate Binary operations parse to Fed instruction</li>
+ <li>FederationUtils.bindResponses causes out of memory because of
sparse matrices.</li>
+ <li>Python IDE test Docs fail</li>
+ <li>MSVM robustness for non-existing classes</li>
+ <li>CLA ArrayOutOfBounds in sample</li>
+ <li>CLA Invalid Unique estimate DDC</li>
+ <li>Federated read cache cannot be disabled</li>
+ <li>Monitoring Heavy hitters not always correct list</li>
+ <li>Slow Federated Mlogreg on Criteo (dummy-coded)</li>
+ <li>Incorrect warning when reading scalars</li>
+ <li>Spark with default settings</li>
+ <li>Cleaning Pipelines: Task Parallel Experiments failing in spark
mode</li>
+ <li>Unique() crashes with iterator EOF on vectors with >1K distinct
items</li>
+ <li>Perftest: Mlogreg on 1M_1k_dense w/ unnecessary spark jobs</li>
+ <li>Perftest: lmDS on 1M_1k_dense with unnecessary spark tsmm</li>
+ <li>Java doc warnings</li>
+ </ul>
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