mrd0ll4r opened a new issue, #46983: URL: https://github.com/apache/arrow/issues/46983
### Describe the bug, including details regarding any error messages, version, and platform. Hello, it's me again :) Not with a big-data crash today, but a different oddity. I have a large-ish parquet dataset, which I process with multiple dplyr verbs, including `inner_join`s. I used to do this in "plain" Arrow, but wanted to try `to_duckdb` for performance (and also because it's cool). I join the dataset to a list of characters and later to a tibble. `join_by` complains if the backends are not the same (I could provide `copy=TRUE`), so I decided to move those to DuckDB, too. However, I noticed that when I execute multiple queries with `inner_join(foo %>% to_duckdb(), ...)`s, DuckDB sometimes doesn't find the referenced table. It's flaky. This is the error: ```R Error in `collect()`: ! Failed to collect lazy table. Caused by error in `dbSendQuery()`: ! rapi_prepare: Failed to prepare query SELECT reason, SUM(n) AS n FROM ( SELECT LHS.*, reason FROM ( SELECT cid, COUNT(*) AS n FROM ( SELECT arrow_107.* FROM arrow_107 INNER JOIN arrow_108 ON (arrow_107.cid = arrow_108.cid) ) q01 GROUP BY cid ) LHS LEFT JOIN arrow_109 ON (LHS.cid = arrow_109.cid) ) q01 GROUP BY reason Error: Catalog Error: Table with name arrow_108 does not exist! Did you mean "pg_proc"? LINE 9: INNER JOIN arrow_108 ^ Run `rlang::last_trace()` to see where the error occurred. > rlang::last_trace() <error/rlang_error> Error in `collect()`: ! Failed to collect lazy table. Caused by error in `dbSendQuery()`: ! rapi_prepare: Failed to prepare query SELECT reason, SUM(n) AS n FROM ( SELECT LHS.*, reason FROM ( SELECT cid, COUNT(*) AS n FROM ( SELECT arrow_107.* FROM arrow_107 INNER JOIN arrow_108 ON (arrow_107.cid = arrow_108.cid) ) q01 GROUP BY cid ) LHS LEFT JOIN arrow_109 ON (LHS.cid = arrow_109.cid) ) q01 GROUP BY reason Error: Catalog Error: Table with name arrow_108 does not exist! Did you mean "pg_proc"? LINE 9: INNER JOIN arrow_108 ^ --- Backtrace: ▆ 1. ├─... %>% collect() 2. ├─dplyr::collect(.) 3. └─dbplyr:::collect.tbl_sql(.) 4. ├─base::withCallingHandlers(...) 5. ├─dbplyr::db_collect(...) 6. └─dbplyr:::db_collect.DBIConnection(...) 7. ├─DBI::dbSendQuery(con, sql) 8. └─duckdb::dbSendQuery(con, sql) ``` The particularly weird thing is that it usually works the first time, but fails when I execute it multiple times one after the other. Is there some GC mechanism at work maybe that kicks in during preparation/execution of the second run? Reproducer: ```R # Probably unrelated, but this is how Arrow was compiled: Sys.setenv("ARROW_WITH_ZLIB"="ON") Sys.setenv("ARROW_PARQUET" = "ON") Sys.setenv("ARROW_WITH_ZSTD" = "ON") Sys.setenv("ARROW_MIMALLOC" = "ON") Sys.setenv("LIBARROW_MINIMAL" = FALSE) Sys.setenv("LIBARROW_BINARY" = FALSE) Sys.setenv("ARROW_R_DEV" = TRUE) Sys.setenv(MAKEFLAGS = sprintf("-j%d", parallel::detectCores())) options(renv.config.pak.enabled = TRUE) # Dependencies: library(arrow) library(dplyr) # I might have forgotten a package here, this is part of a larger project foo1 <- arrow_table(cid = c("a","b","c", "d", "a"), peer = c("1","2","3","2","2")) foo2 <- c("b","c") foo3 <- tibble(cid=c("a","b","c","d"), reason=c("something","something else","something else","something")) # This fails most of the time. # In particular if you execute it multiple times quickly in succession. foo1 %>% to_duckdb() %>% inner_join(arrow_table(tibble(cid=foo2)) %>% to_duckdb(), by=join_by(cid)) %>% group_by(cid) %>% tally() %>% left_join(arrow_table(foo3) %>% to_duckdb(), by=join_by(cid)) %>% group_by(reason) %>% summarize(n=sum(n)) %>% collect() # This works more often, but still fails sometimes: foo1 %>% to_duckdb() %>% inner_join(arrow_table(tibble(cid=foo2)) %>% to_duckdb(), by=join_by(cid)) %>% group_by(cid) %>% tally() %>% left_join(arrow_table(foo3) %>% to_duckdb(), by=join_by(cid)) %>% collect() # Pulling out the inline to_duckdb calls makes it so that it seemingly always works: tmp1 <- arrow_table(tibble(cid=foo2)) %>% to_duckdb() tmp2 <- arrow_table(foo3) %>% to_duckdb() foo1 %>% to_duckdb() %>% inner_join(tmp1, by=join_by(cid)) %>% group_by(cid) %>% tally() %>% left_join(tmp2, by=join_by(cid)) %>% group_by(reason) %>% summarize(n=sum(n)) %>% collect() ``` ### Additional Info #### Machine Overview: ``` Memory: 378 GB CPU: 64x Intel(R) Xeon(R) Gold 6154 OS: Debian 12 ``` #### R `sessionInfo()` ```R > sessionInfo() R version 4.5.0 (2025-04-11) Platform: x86_64-pc-linux-gnu Running under: Debian GNU/Linux 12 (bookworm) Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 LAPACK version 3.11.0 locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 [4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C [10] LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C time zone: Europe/Berlin tzcode source: system (glibc) attached base packages: [1] stats graphics grDevices datasets utils methods base other attached packages: [1] treemapify_2.5.6 paletteer_1.6.0 ggplot2_3.5.2 viridis_0.6.5 [5] viridisLite_0.4.2 pracma_2.4.4 xtable_1.8-4 forcats_1.0.0 [9] readr_2.1.5 arrow_20.0.0 tidyr_1.3.1 stringr_1.5.1 [13] lubridate_1.9.4 dplyr_1.1.4 loaded via a namespace (and not attached): [1] utf8_1.2.6 generics_0.1.4 renv_1.0.3 stringi_1.8.7 [5] hms_1.1.3 magrittr_2.0.3 grid_4.5.0 timechange_0.3.0 [9] RColorBrewer_1.1-3 blob_1.2.4 DBI_1.2.3 rematch2_2.1.2 [13] gridExtra_2.3 purrr_1.0.4 scales_1.4.0 duckdb_1.3.0 [17] cli_3.6.5 rlang_1.1.6 crayon_1.5.3 dbplyr_2.5.0 [21] bit64_4.6.0-1 withr_3.0.2 tools_4.5.0 parallel_4.5.0 [25] tzdb_0.5.0 assertthat_0.2.1 vctrs_0.6.5 R6_2.6.1 [29] lifecycle_1.0.4 bit_4.6.0 vroom_1.6.5 pkgconfig_2.0.3 [33] pillar_1.10.2 gtable_0.3.6 glue_1.8.0 ggfittext_0.10.2 [37] tibble_3.3.0 tidyselect_1.2.1 rstudioapi_0.17.1 farver_2.1.2 [41] compiler_4.5.0 ``` #### `lsb_release -a` ``` No LSB modules are available. Distributor ID: Debian Description: Debian GNU/Linux 12 (bookworm) Release: 12 Codename: bookworm ``` #### `uname -a` ``` Linux <redacted> 6.1.0-34-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.1.135-1 (2025-04-25) x86_64 GNU/Linux ``` #### `cat /proc/cpuinfo` (truncated) ``` processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 85 model name : Intel(R) Xeon(R) Gold 6154 CPU @ 3.00GHz stepping : 4 microcode : 0x2007108 cpu MHz : 2992.968 cache size : 16384 KB physical id : 0 siblings : 64 core id : 0 cpu cores : 64 apicid : 0 initial apicid : 0 fpu : yes fpu_exception : yes cpuid level : 22 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon rep_good nopl xtopology cpuid tsc_known_freq pni pclmulqdq vmx ssse3 fma cx16 pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault invpcid_single pti ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat umip pku ospke md_clear flush_l1d arch_capabilities vmx flags : vnmi preemption_timer posted_intr invvpid ept_x_only ept_ad ept_1gb flexpriority apicv tsc_offset vtpr mtf vapic ept vpid unrestricted_guest vapic_reg vid shadow_vmcs pml tsc_scaling bugs : cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf mds swapgs taa mmio_stale_data retbleed gds bhi ibpb_no_ret bogomips : 5985.93 clflush size : 64 cache_alignment : 64 address sizes : 46 bits physical, 48 bits virtual power management: ``` ### Component(s) R -- This is an automated message from the Apache Git Service. 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