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Update query parser to infer strings as ascii #277

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Merged
eddelbuettel merged 7 commits into from
Jul 30, 2021
Merged

Update query parser to infer strings as ascii #277

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befa40a
Query parser now detects ascii values w/ digits
aaronwolen Jul 29, 2021
01e2464
Fix query parser ascii detection test
aaronwolen Jul 29, 2021
1c22f8b
More improvements to query parser's ascii detection
aaronwolen Jul 29, 2021
1270726
Re-add query parser's underscore detection
aaronwolen Jul 29, 2021
cf587dd
Further refinement to qc parser type inference
aaronwolen Jul 30, 2021
8fb56d1
Additital edge case test for qc parser
aaronwolen Jul 30, 2021
381907e
restore .isAscii
eddelbuettel Jul 30, 2021
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12 changes: 6 additions & 6 deletions R/QueryCondition.R
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Original file line number Diff line number Diff line change
Expand Up @@ -107,13 +107,13 @@ tiledb_query_condition_combine <- function(lhs, rhs, op) {
parse_query_condition <- function(expr, debug=FALSE) {
.isComparisonOperator <- function(x) as.character(x) %in% c(">", ">=", "<", "<=", "==", "!=")
.isBooleanOperator <- function(x) as.character(x) %in% c("&&", "||", "!")
.isAscii <- function(x) grepl("^[a-zA-Z_]*$", x)
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@eddelbuettel eddelbuettel Jul 29, 2021

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Do we want to keep the front anchor? Column names cannot start with digits...

Maybe "^[a-zA-Z_0-9]*" ?

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@aaronwolen aaronwolen Jul 29, 2021

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But this is checking column values, right? So we don't want to miss something like "1a".

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@eddelbuettel eddelbuettel Jul 29, 2021

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Gosh, you're right. I was so focussed on schema names.

In which case it is 'much worse' :) I.e. possibly payload is much more. Should we use [[:alpha:]] or a totally generic reg exp (meta) pattern.

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@aaronwolen aaronwolen Jul 29, 2021

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Sure, I like [[:alpha:]]. It should improve detection for non-a-z characters too! I'll update.

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@eddelbuettel eddelbuettel Jul 29, 2021

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Per ?regexp maybe [[:alnum:]] ?

.isInteger <- function(x) as.character(as.integer(x)) == x
.isDouble <- function(x) as.character(as.numeric(x)) == x && grepl("[\\.]", as.character(x))
.isAscii <- function(x) grepl("^[[:alnum:]_]+$", x)
.isInteger <- function(x) grepl("^[[:digit:]]+$", as.character(x))
.isDouble <- function(x) grepl("^[[:digit:]\\.]+$", as.character(x)) && length(grepRaw(".", as.character(x), fixed = TRUE, all = TRUE)) == 1
.getType <- function(x) {
if (.isAscii(as.character(x))) "ASCII"
else if (.isDouble(as.character(x))) "FLOAT64"
else "INT32"
if (isTRUE(.isInteger(x))) "INT32"
else if (isTRUE(.isDouble(x))) "FLOAT64"
else "ASCII"
}
.mapOpToCharacter <- function(x) switch(x,
`>` = "GT",
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24 changes: 24 additions & 0 deletions inst/tinytest/test_querycondition.R
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Expand Up @@ -194,3 +194,27 @@ arrwithqc <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
res <- arrwithqc[]
expect_equal(NROW(res), 165L)
expect_true(all(res$sex != "male"))

## check type inference for edge cases
edgecases <- data.frame(x1 = "a1", x2 = 1L, x3 = "_1", x4 = "1.1.1")

uri <- tempfile()
fromDataFrame(edgecases, uri, sparse=TRUE)

qcx1 <- tiledb::parse_query_condition(x1 == "a1")
arrx1 <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qcx1)
res <- arrx1[]
expect_equal(res$x1, "a1")

qcx2 <- tiledb::parse_query_condition(x2 == 1L)
arrx2 <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qcx2)
res <- arrx2[]
expect_equal(res$x2, 1L)

qcx3 <- tiledb::parse_query_condition(x3 == "_1")
arrx3 <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qcx3)
expect_equal(arrx3[]$x3, "_1")

qcx4 <- tiledb::parse_query_condition(x4 == "1.1.1")
arrx4 <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qcx4)
expect_equal(arrx4[]$x4, "1.1.1")