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verification – Verifying Old Transaction in Bitcoin Core’s console -getrawtransactions does return “no such mempool transaction” error

You’re trying to use an optional feature of Bitcoin Core: the ability to query for old transactions.

This functionality needs:

  • (a) the full blockchain (where else would it get the transaction from)
  • (b) an index by txid so it doesn’t need to read through 270 GB to find what you’re looking for.

The error message you get is telling you that this (b) index is not enabled. When you try to enable it, it fails because you don’t actually have the blockchain (a) in the first place (it’s pruned), so it can’t be indexed.

If you really need this functionality, you’ll need to disable pruning, start syncing from scratch (as it’ll need to download the blockchain again), and enable indexing.

However, you saying “tried to verify” perhaps highlights a misconception you have: getrawtransaction doesn’t verify anything, it just retrieves the transaction in your local copy of the blockchain. Everything is already verified, even when it’s not kept on disk. Generally when you care about a particular transaction, it’s because it directly or indirectly affects your own funds, and the recommended solution for that is simply using good wallet software – it will only show you transactions that are verified and whose entire history is verified.

Cannot break loop over cores using do parallel in R

I am trying to break this loop over multiple cores. For each loop i is sequentially changed from 1 to 16. At the moment it isn’t breaking over the cores. Thank you for your help!

cl <- makeCluster((detectCores()-2))
registerDoParallel(cl)                 

clusters <- 1:16

foreach(i = clusters, .packages = c("tidyverse","magrittr")) %dopar% {

Encode.all.cl <-  Encode.all.t %>%
filter(cluster == i) %>%
select(-cluster)

Encode.all.cl.2 <- data.frame(t(Encode.all.cl)) %>%
set_rownames(colnames(Encode.all.cl)) %>%
set_colnames(rownames(Encode.all.cl))


Encode.all.cl.3 <- Encode.all.cl.2 %>%
mutate(.,count = rowSums(Encode.all.cl.2)) %>%
set_rownames(colnames(Encode.all.cl)) %>%
set_colnames(c(rownames(Encode.all.cl), "count")) %>%
filter(., count >= ncol(Encode.all.cl.2)*0.9) %>% #common in 90% of peaks
rownames_to_column(var = "Peak") %>%
dplyr::select(Peak) %>%
set_colnames("Cluster")

consensusPeaks((i)) <- Encode.all.cl.3

print(paste0("Finished cluster ", i))

}

stopCluster(cl)

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parallelization – Mathematica Parellel on SuperComputer by specifying the number of Cores available to user

I am running following program on mathematica 9.0

Sample program: ParallelTable(Exp(Sin(x))^Sin(x),{x,0.1,6000,0.1});

installed on Supercomputer through Mobaxterm (which is terminal interface) using this:

nohup math -run -noprompt < samplecode.m.

Which gives the result on terminal after saying "Launching kernels..."

As I know that one has to specify the number of cores available for computation to user in order to utilized those cores, and then submitted jobs goes into a queue and gets evaluated after queue is clear.

Since I haven’t specified the number of cores in above piece of code, So it must be using single core.

Now can anyone tell me in simple terms,

a) How to specify number of available cores and run above sample code for parallel computation so that it is utilizing all the available cores to the user.

$ProcessorCount says 40

Note: Starting half of this answer might be related to my ques.

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