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Spark 2* union_all has issues ( https://github.com/WinVector/replyr/blob/master/issues/UnionIssue.md ), and exponsed union_all semantics differ from data-source backend to backend. This is an attempt to provide a join-based replacement.
replyr_union_all(tabA, tabB, ..., useDplyrLocal = TRUE, useSparkRbind = TRUE, tempNameGenerator = makeTempNameGenerator("replyr_union_all"))
not-NULL table with at least 1 row.
not-NULL table with at least 1 row on same data source as tabA and commmon columns.
force later arguments to be bound by name.
logical if TRUE use dplyr::bind_rows for local data.
logical if TRUE try to use rbind on Sparklyr data
temp name generator produced by replyr::makeTempNameGenerator, used to record dplyr::compute() effects.
table with all rows of tabA and tabB (union_all).
# NOT RUN { d1 <- data.frame(x = c('a','b'), y = 1, stringsAsFactors= FALSE) d2 <- data.frame(x = 'c', z = 1, stringsAsFactors= FALSE) replyr_union_all(d1, d2, useDplyrLocal= FALSE) # }
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