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Understanding Parquet, Iceberg and Data Lakehouses at Broad

In the past few years, I've heard a lot about Avro, Parquet, ORC, Arrow and Feather, but I also keep hearing about Iceberg and Delta Lake. As a "database person", I’ve been struggling to understand all of these different things, and how they relate to Data Lakes and Data ....

Presto Trino , Vladimir Sivcevic , Rowstore Columnstore , Cloud Blob , Data Lakes , Data Lakehouses , Data Gets Stored , Apache Arrow , Apache Parquet , Big Data , Apache Drill , Hive Format , Delta Lake , Confluent Schema Registry , Hive Metastore , Iceberg Catalogs , Unity Catalog , Query Optimization , Data Lake , Data Warehouse , Cloud Blob Store , Data Lakehouse , Apache Iceberg ,

"CREAM: Named Entity Recognition with Concise query and REgion-Aware Mi" by Xun Yao, Qihang Yang et al.

Recent advancements in Machine Reading Comprehension (MRC) models have sparked interest in the field of Named Entity Recognition (NER), where entities are extracted as answers of given queries. Yet, existing MRC-based models face several challenges, including high computational costs, limited consideration of entity content information, and the tendency to generate sharp boundaries, that hinder their generalizability. To alleviate these issues, this paper introduces CREAM, an enhanced model leveraging Concise query and REgion-Aware Minimization. First, we propose a simple yet effective strategy of generating concise queries based primarily on entity categories. Second, we propose to go beyond existing methods by identifying entire entities, instead of just their boundaries (start and end positions), with an efficient continuous cross-entropy loss. An in-depth analysis is further provided to reveal their benefit. The proposed method is evaluated on six well-known NER benchmarks. Experim ....

Machine Reading Comprehension , Named Entity Recognition , Named Entity Recognition , Query Optimization , Egion Aware Loss ,