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new 0f99027c2f5 [SPARK-40547][DOCS] Fix dead links in sparkr-vignettes.Rmd
0f99027c2f5 is described below
commit 0f99027c2f527f4221822e5863b8b8fe4e3a1cfc
Author: Yuming Wang <[email protected]>
AuthorDate: Fri Sep 23 08:57:59 2022 -0700
[SPARK-40547][DOCS] Fix dead links in sparkr-vignettes.Rmd
### What changes were proposed in this pull request?
This PR fix all dead links in sparkr-vignettes.Rmd.
### Why are the changes needed?
binary-release-hadoop3.log logs:
```
yumwangLM-SHC-16508156 output % tail -n 30 binary-release-hadoop3.log
* this is package ‘SparkR’ version ‘3.3.1’
* package encoding: UTF-8
* checking CRAN incoming feasibility ... NOTE
Maintainer: ‘The Apache Software Foundation <devspark.apache.org>’
New submission
Package was archived on CRAN
CRAN repository db overrides:
X-CRAN-Comment: Archived on 2021-06-28 as issues were not corrected
in time.
Should use tools::R_user_dir().
Found the following (possibly) invalid URLs:
URL:
https://spark.apache.org/docs/latest/api/R/column_aggregate_functions.html
From: inst/doc/sparkr-vignettes.html
Status: 404
Message: Not Found
URL: https://spark.apache.org/docs/latest/api/R/read.df.html
From: inst/doc/sparkr-vignettes.html
Status: 404
Message: Not Found
URL: https://spark.apache.org/docs/latest/api/R/sparkR.session.html
From: inst/doc/sparkr-vignettes.html
Status: 404
Message: Not Found
* checking package namespace information ... OK
* checking package dependencies ...%
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
manual test.
Closes #37983 from wangyum/fix-links.
Authored-by: Yuming Wang <[email protected]>
Signed-off-by: Dongjoon Hyun <[email protected]>
(cherry picked from commit 7d13d467a88521c81dfbd9453edda444a13e8855)
Signed-off-by: Dongjoon Hyun <[email protected]>
---
R/pkg/vignettes/sparkr-vignettes.Rmd | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/R/pkg/vignettes/sparkr-vignettes.Rmd
b/R/pkg/vignettes/sparkr-vignettes.Rmd
index 1f3dd13353f..4a510763afb 100644
--- a/R/pkg/vignettes/sparkr-vignettes.Rmd
+++ b/R/pkg/vignettes/sparkr-vignettes.Rmd
@@ -170,7 +170,7 @@ sparkR.session(sparkHome = "/HOME/spark")
### Spark Session {#SetupSparkSession}
-In addition to `sparkHome`, many other options can be specified in
`sparkR.session`. For a complete list, see [Starting up:
SparkSession](https://spark.apache.org/docs/latest/sparkr.html#starting-up-sparksession)
and [SparkR API
doc](https://spark.apache.org/docs/latest/api/R/sparkR.session.html).
+In addition to `sparkHome`, many other options can be specified in
`sparkR.session`. For a complete list, see [Starting up:
SparkSession](https://spark.apache.org/docs/latest/sparkr.html#starting-up-sparksession)
and [SparkR API
doc](https://spark.apache.org/docs/latest/api/R/reference/sparkR.session.html).
In particular, the following Spark driver properties can be set in
`sparkConfig`.
@@ -231,7 +231,7 @@ The general method for creating `SparkDataFrame` from data
sources is `read.df`.
sparkR.session(sparkPackages = "com.databricks:spark-avro_2.12:3.0.0")
```
-We can see how to use data sources using an example CSV input file. For more
information please refer to SparkR
[read.df](https://spark.apache.org/docs/latest/api/R/read.df.html) API
documentation.
+We can see how to use data sources using an example CSV input file. For more
information please refer to SparkR
[read.df](https://spark.apache.org/docs/latest/api/R/reference/read.df.html)
API documentation.
```{r, eval=FALSE}
df <- read.df(csvPath, "csv", header = "true", inferSchema = "true",
na.strings = "NA")
```
@@ -340,7 +340,7 @@ A common flow of grouping and aggregation is
2. Feed the `GroupedData` object to `agg` or `summarize` functions, with some
provided aggregation functions to compute a number within each group.
-A number of widely used functions are supported to aggregate data after
grouping, including `avg`, `count_distinct`, `count`, `first`, `kurtosis`,
`last`, `max`, `mean`, `min`, `sd`, `skewness`, `stddev_pop`, `stddev_samp`,
`sum_distinct`, `sum`, `var_pop`, `var_samp`, `var`. See the [API doc for
aggregate
functions](https://spark.apache.org/docs/latest/api/R/column_aggregate_functions.html)
linked there.
+A number of widely used functions are supported to aggregate data after
grouping, including `avg`, `count_distinct`, `count`, `first`, `kurtosis`,
`last`, `max`, `mean`, `min`, `sd`, `skewness`, `stddev_pop`, `stddev_samp`,
`sum_distinct`, `sum`, `var_pop`, `var_samp`, `var`. See the [API doc for
aggregate
functions](https://spark.apache.org/docs/latest/api/R/reference/column_aggregate_functions.html)
linked there.
For example we can compute a histogram of the number of cylinders in the
`mtcars` dataset as shown below.
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