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#' Backend: Impala
#'
#' @description
#' See `vignette("translation-function")` and `vignette("translation-verb")` for
#' details of overall translation technology. Key differences for this backend
#' are a scattering of custom translations provided by users, mostly focussed
#' on bitwise operations.
#'
#' Use `simulate_impala()` with `lazy_frame()` to see simulated SQL without
#' converting to live access database.
#'
#' @name backend-impala
#' @aliases NULL
#' @examples
#' library(dplyr, warn.conflicts = FALSE)
#'
#' lf <- lazy_frame(a = TRUE, b = 1, c = 2, d = "z", con = simulate_impala())
#' lf %>% transmute(X = bitwNot(bitwOr(b, c)))
NULL
#' @export
#' @rdname simulate_dbi
simulate_impala <- function() simulate_dbi("Impala")
#' @export
dbplyr_edition.Impala <- function(con) {
2L
}
#' @export
sql_translation.Impala <- function(con) {
sql_variant(
scalar = sql_translator(.parent = base_odbc_scalar,
bitwNot = sql_prefix("BITNOT", 1),
bitwAnd = sql_prefix("BITAND", 2),
bitwOr = sql_prefix("BITOR", 2),
bitwXor = sql_prefix("BITXOR", 2),
bitwShiftL = sql_prefix("SHIFTLEFT", 2),
bitwShiftR = sql_prefix("SHIFTRIGHT", 2),
as.Date = sql_cast("VARCHAR(10)"),
ceiling = sql_prefix("CEIL")
) ,
base_odbc_agg,
base_odbc_win
)
}
#' @export
sql_table_analyze.Impala <- function(con, table, ...) {
# Using COMPUTE STATS instead of ANALYZE as recommended in this article
# https://www.cloudera.com/documentation/enterprise/5-9-x/topics/impala_compute_stats.html
build_sql("COMPUTE STATS ", as.sql(table, con = con), con = con)
}
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