{ "_id": "6a0f6facacfb0bcc41c5f275", "Package": "ibmdbR", "Version": "1.51.0", "Title": "IBM in-Database Analytics for R", "Authors@R": "c(\nperson(\"Shaikh\", \"Quader\", role = c(\"aut\", \"cre\"), email = \"db2-analytics@de.ibm.com\"),\nperson(\"Toni\", \"Bollinger\", role = c(\"aut\")),\nperson(\"Ming-pang\", \"Wei\", role = c(\"aut\")),\nperson(\"Alexander\", \"Eckert\", role = c(\"aut\")),\nperson(\"Michael\", \"Wurst\", role = c(\"aut\")),\nperson(\"Craig\", \"Blaha\", role = c(\"ctb\"), comment = \"documentation\"),\nperson(\"IBM Corporation\", role = c(\"cph\"), email = \"db2-analytics@de.ibm.com\")\n)", "VignetteBuilder": "knitr", "Description": "Functionality required to efficiently use R with IBM(R)\nDb2(R) Warehouse offerings (formerly IBM dashDB(R)) and IBM Db2\nfor z/OS(R) in conjunction with IBM Db2 Analytics Accelerator\nfor z/OS. Many basic and complex R operations are pushed down\ninto the database, which removes the main memory boundary of R\nand allows to make full use of parallel processing in the\nunderlying database. For executing R-functions in a multi-node\nenvironment in parallel the idaTApply() function requires the\n'SparkR' package\n(). 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