Abstract:

information

  • Iconiq has led a $100 million investment in Snowflake Computing, a cloud-based database company that stores and queries data for analysts to use BI tools for analysis. The company recently announced a $100 million funding round.
  • More development planning in 14 provinces and cities for big data output target before 2.8 trillion, data center union council for the promotion of development of big data, according to a report issued by the China big data are forming five industry agglomeration area, eliminate repetition factor, have been identified in 2020 big data industry scale goal planning in 14 provinces combined has amounted to 2.84 trillion yuan, Far beyond the goal of the country’s overall plan.
  • This conference will combine the national policies and the advantages and disadvantages of Artificial intelligence in China to conduct an in-depth analysis of the technology and market itself, analyze the current development barriers of ARTIFICIAL intelligence, clarify the market accessibility of artificial intelligence, and point out the direction for the development of enterprises.
  • Data has increasingly become the underlying architecture and core infrastructure of each platform. The big data mode of Internet finance has ten modes, including anti-fraud, rating, credit investigation, data bank data platform, non-performing asset disposal and asset securitization.
  • (Technology) Three common misconceptions about Apache Spark Three common misconceptions about Apache Spark are as follows: Spark is a memory technology, Spark is 10x to 100x faster than Hadoop, and Spark introduces a new technology in data processing.
  • This article focuses on the new features and improvements of Hadoop 3.0, the incompatible changes of Hadoop 3.0 and their impact on users, the latest trends in the Hadoop open source community, and the future prospects of Hadoop.
  • ApacheKylin introduces a series of advanced Settings to help users filter out the cuboids they really need to ease the pressure of Cube construction. These Settings include aggregation groups, union dimensions, hierarchy dimensions, and necessary dimensions. This paper mainly introduces the realization principle and application scenarios of the united dimension.
  • Bigdata-join has predicates that push down? Jion algorithm selection, Join order selection and Join algorithm optimization all have great influence on Join performance. The essence of the Runtime Filter described in this article is to use predicates (BloomFilter) to push down and reduce the amount of data actually participating in a Join by filtering the participating tables.