I’ve been drafting a new R package — [`sergeant`](https:\/\/github.com\/hrbrmstr\/sergeant) — to work with [Apache Drill](http:\/\/drill.apache.org\/) and have found it much easier to manage having Drill operating in a single node cluster vs `drill-embedded` mode (esp when I need to add a couple more nodes for additional capacity). That means running [Apache Zookeeper](https:\/\/zookeeper.apache.org\/) and I’ve had the occasional need to ping the Zookeeper process to see various stats (especially when I add some systems to the cluster). <\/p>\n
Yes, it’s very easy+straightforward to `nc hostname 2181` from the command line to issue commands (or use the Zookeeper CLIs) but when I’m in R I like to stay in R. To that end, I made a small reference class that makes it super-easy to query Zookeeper from within R. Said class will eventually be in a sister package to `sergeant` (and, a more detailed post on `sergeant` is forthcoming), but there may be others who want\/need to poke at Zookeeper processes with [4-letter words](https:\/\/zookeeper.apache.org\/doc\/trunk\/zookeeperAdmin.html#sc_zkCommands) and this will help you stay within R. The only command not available is `stmk` since I don’t have the pressing need to set the trace mask. <\/p>\n
After you source the self-contained reference class you connect and then issue commands as so:<\/p>\n
zk <- zookeeper$new(host="drill.local")\r\n\r\nzk$ruok()\r\n\r\nzk$conf()\r\nzk$stat()<\/code><\/pre>\nDrop a note in the comments (since this isn’t on github, yet) with any questions\/issues.<\/p>\n
zookeeper <- setRefClass(\r\n\r\n Class="zookeeper",\r\n\r\n fields=list(\r\n host="character",\r\n port="integer",\r\n timeout="integer"\r\n ),\r\n\r\n methods=list(\r\n\r\n initialize=function(..., host="localhost", port=2181L, timeout=30L) {\r\n host <<- host ; port <<- port ; timeout <<- timeout; callSuper(...)\r\n },\r\n\r\n available_commands=function() {\r\n return(sort(c("conf", "envi", "stat", "srvr", "whcs", "wchc", "wchp", "mntr",\r\n "cons", "crst", "srst", "dump", "ruok", "dirs", "isro", "gtmk")))\r\n },\r\n\r\n connect=function(host="localhost", port=2181L, timeout=30L) {\r\n .self$host <- host ; .self$port <- port ; .self$timeout <- timeout\r\n },\r\n\r\n conf=function() {\r\n res <- .self$send_cmd("conf")\r\n res <- stringi::stri_split_fixed(res, "=", 2, simplify=TRUE)\r\n as.list(setNames(res[,2], res[,1]))\r\n },\r\n\r\n envi=function() {\r\n res <- .self$send_cmd("envi")\r\n res <- stringi::stri_split_fixed(res[-1], "=", 2, simplify=TRUE)\r\n as.list(setNames(res[,2], res[,1]))\r\n },\r\n\r\n stat=function() {\r\n res <- .self$send_cmd("stat")\r\n version <- stri_replace_first_regex(res[1], "^Zoo.*: ", "")\r\n res <- res[-(1:2)]\r\n sep <- which(res=="")\r\n clients <- stri_trim(res[1:(sep-1)])\r\n zstats <- stringi::stri_split_fixed(res[(sep+1):length(res)], ": ", 2, simplify=TRUE)\r\n zstats <- as.list(setNames(zstats[,2], zstats[,1]))\r\n list(version=version, clients=clients, stats=zstats)\r\n },\r\n\r\n srvr=function() {\r\n res <- .self$send_cmd("srvr")\r\n zstats <- stringi::stri_split_fixed(res, ": ", 2, simplify=TRUE)\r\n as.list(setNames(zstats[,2], zstats[,1]))\r\n },\r\n\r\n wchs=function() {\r\n res <- .self$send_cmd("wchs")\r\n conn_path <- stri_match_first_regex(res[1], "^([[:digit:]]+) connections watching ([[:digit:]]+) paths")\r\n tot_watch <- stri_match_first_regex(res[2], "Total watches:([[:digit:]]+)")\r\n list(connections_watching=conn_path[,2], paths=conn_path[,3], total_watches=tot_watch[,2])\r\n },\r\n\r\n wchc=function() {\r\n stri_trim(.self$send_cmd("wchc")) %>% discard(`==`, "") -> res\r\n setNames(list(res[2:length(res)]), res[1])\r\n },\r\n\r\n wchp=function() {\r\n .self$send_cmd("wchp") %>% stri_trim() %>% discard(`==`, "") -> res\r\n data.frame(\r\n path=qq[seq(1, length(qq), 2)],\r\n address=qq[seq(2, length(qq), 2)],\r\n stringsAsFactors=FALSE\r\n )\r\n },\r\n\r\n mntr=function() {\r\n res <- .self$send_cmd("mntr")\r\n res <- stringi::stri_split_fixed(res, "\\t", 2, simplify=TRUE)\r\n as.list(setNames(res[,2], res[,1]))\r\n },\r\n\r\n cons=function() { list(clients=stri_trim(.self$send_cmd("cons") %>% discard(`==`, ""))) },\r\n crst=function() { message(.self$send_cmd("crst")) ; invisible() },\r\n srst=function() { message(.self$send_cmd("srst")) ; invisible() },\r\n dump=function() { paste0(.self$send_cmd("dump"), collapse="\\n") },\r\n ruok=function() { .self$send_cmd("ruok") == "imok" },\r\n dirs=function() { .self$send_cmd("dirs") },\r\n isro=function() { .self$send_cmd("isro") },\r\n gtmk=function() { R.utils::intToBin(as.integer(.self$send_cmd("gtmk"))) },\r\n\r\n send_cmd=function(cmd) {\r\n require(purrr)\r\n require(stringi)\r\n require(R.utils)\r\n sock <- purrr::safely(socketConnection)\r\n con <- sock(host=.self$host, port=.self$port, blocking=TRUE, open="r+", timeout=.self$timeout)\r\n if (!is.null(con$result)) {\r\n con <- con$result\r\n cat(cmd, file=con)\r\n response <- readLines(con, warn=FALSE)\r\n a <- try(close(con))\r\n purrr::flatten_chr(stringi::stri_split_lines(response))\r\n } else {\r\n warning(sprintf("Error connecting to [%s:%s]", host, port))\r\n }\r\n }\r\n\r\n )\r\n\r\n)<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"I’ve been drafting a new R package — [`sergeant`](https:\/\/github.com\/hrbrmstr\/sergeant) — to work with [Apache Drill](http:\/\/drill.apache.org\/) and have found it much easier to manage having Drill operating in a single node cluster vs `drill-embedded` mode (esp when I need to add a couple more nodes for additional capacity). That means running [Apache Zookeeper](https:\/\/zookeeper.apache.org\/) and I’ve had […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":true,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"activitypub_content_warning":"","activitypub_content_visibility":"","activitypub_max_image_attachments":3,"activitypub_interaction_policy_quote":"anyone","activitypub_status":"","footnotes":""},"categories":[91],"tags":[810],"class_list":["post-4721","post","type-post","status-publish","format-standard","hentry","category-r","tag-post"],"yoast_head":"\n
Minding the zoo[keeper] with R - rud.is<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/rud.is\/b\/2016\/12\/16\/minding-the-zookeeper-with-r\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Minding the zoo[keeper] with R - rud.is\" \/>\n<meta property=\"og:description\" content=\"I’ve been drafting a new R package — [`sergeant`](https:\/\/github.com\/hrbrmstr\/sergeant) — to work with [Apache Drill](http:\/\/drill.apache.org\/) and have found it much easier to manage having Drill operating in a single node cluster vs `drill-embedded` mode (esp when I need to add a couple more nodes for additional capacity). 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Make Parquet Files Great Again in R)","author":"hrbrmstr","date":"2017-01-22","format":false,"excerpt":"2021-11-04 UPDATE: Just use {arrow}. Apache Drill is a nice tool to have in the toolbox as it provides a SQL front-end to a wide array of database and file back-ends and runs in standalone\/embedded mode on every modern operating system (i.e. you can get started with or play locally\u2026","rel":"","context":"In "Apache Drill"","block_context":{"text":"Apache Drill","link":"https:\/\/rud.is\/b\/category\/apache-drill\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":4753,"url":"https:\/\/rud.is\/b\/2016\/12\/20\/sergeant-a-r-boot-camp-for-apache-drill\/","url_meta":{"origin":4721,"position":2},"title":"sergeant : An R Boot Camp for Apache Drill","author":"hrbrmstr","date":"2016-12-20","format":false,"excerpt":"I recently mentioned that I've been working on a development version of an Apache Drill R package called sergeant. Here's a lifted \"TLDR\" on Drill: Drill supports a variety of NoSQL databases and file systems, including HBase, MongoDB, MapR-DB, HDFS, MapR-FS, Amazon S3, Azure Blob Storage, Google Cloud Storage, Swift,\u2026","rel":"","context":"In "Apache Drill"","block_context":{"text":"Apache Drill","link":"https:\/\/rud.is\/b\/category\/apache-drill\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":6111,"url":"https:\/\/rud.is\/b\/2017\/07\/17\/ten-hut-the-apache-drill-r-interface-package-sergeant-is-now-on-cran\/","url_meta":{"origin":4721,"position":3},"title":"Ten-HUT! The Apache Drill R interface package \u2014\u00a0sergeant \u2014\u00a0is now on CRAN","author":"hrbrmstr","date":"2017-07-17","format":false,"excerpt":"I'm extremely pleased to announce that the sergeant package is now on CRAN or will be hitting your local CRAN mirror soon. sergeant provides JDBC, DBI and dplyr\/dbplyr interfaces to Apache Drill. I've also wrapped a few goodies into the dplyr custom functions that work with Drill and if you\u2026","rel":"","context":"In "Apache Drill"","block_context":{"text":"Apache Drill","link":"https:\/\/rud.is\/b\/category\/apache-drill\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":12855,"url":"https:\/\/rud.is\/b\/2020\/11\/20\/updated-apache-drill-r-jdbc-interface-package-sergeant-caffeinated-with-dbplyr-2-x-compatibility\/","url_meta":{"origin":4721,"position":4},"title":"Updated Apache Drill R JDBC Interface Package {sergeant.caffeinated} With {dbplyr} 2.x Compatibility","author":"hrbrmstr","date":"2020-11-20","format":false,"excerpt":"While the future of the Apache Drill ecosystem is somewhat in-play (MapR \u2014 a major sponsoring org for the project \u2014 is kinda dead), I still use it almost daily (on my local home office cluster) to avoid handing over any more money to Amazon than I\/we already do. The\u2026","rel":"","context":"In "Apache Drill"","block_context":{"text":"Apache Drill","link":"https:\/\/rud.is\/b\/category\/apache-drill\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":7637,"url":"https:\/\/rud.is\/b\/2017\/12\/20\/r%e2%81%b6-series-random-sampling-from-apache-drill-tables-with-r-sergeant\/","url_meta":{"origin":4721,"position":5},"title":"R\u2076 Series \u2014 Random Sampling From Apache Drill Tables With R & sergeant","author":"hrbrmstr","date":"2017-12-20","format":false,"excerpt":"(For first-timers, R\u2076 tagged posts are short & sweet with minimal expository; R\u2076 feed) At work-work I mostly deal with medium-to-large-ish data. I often want to poke at new or existing data sets w\/o working across billions of rows. I also use Apache Drill for much of my exploratory work.\u2026","rel":"","context":"In "Apache Drill"","block_context":{"text":"Apache Drill","link":"https:\/\/rud.is\/b\/category\/apache-drill\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/posts\/4721","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/comments?post=4721"}],"version-history":[{"count":0,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/posts\/4721\/revisions"}],"wp:attachment":[{"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/media?parent=4721"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/categories?post=4721"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/tags?post=4721"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}