9 Calculate New Allocations
- add 1,000 to all with at least 0.00001 in queries_proportion_per_indexer from rewards_info
- add 100 at a time to the best one
- re-calculate proportions and keep adding 100 at a time
- when a single one reaches 10% of total, stop adding to that one
- add to others using the same approach until out of available tokens
First, let’s set all new allocations to 0 as a start:
Next, let’s establish a maximum allocation size as 10% of our total stake. This helps spread our allocations across a larger number of subgraphs and avoid our APR from fluctuating as much after we have set the allocations:
## [1] 108387.1Before the next step, let’s make sure to fill in NAs with 0’s to avoid issues when calculating the new allocations:
synced_subgraphs = synced_subgraphs %>%
replace_na(list(
queries_per_indexer = 0,
unique_indexers = 0,
signalled_tokens = 0,
total_allocated_tokens = 0,
rewards_proportion = 0,
sum_queries = 0
))Now let’s start allocating some tokens. We will
synced_subgraphs %<>%
# for cases with more than 2 signal but less than 1000 in staked tokens, add a 1,000 allocation
mutate(new_allocation = case_when( signalled_tokens > 3 && total_allocated_tokens < 1000 ~ 1000,
# for cases with more than 50,000 queries per indexer, add 1000 allocation
queries_per_indexer > 50000 ~ 1000,
# for cases with less than 3 signal (but more than 0.5) and less than 1000 in staked tokens, add a 100 allocation
(signalled_tokens < 3 | signalled_tokens > 0.5) && total_allocated_tokens < 1000 ~ 100,
# everything else remains with the old new_allocation value
TRUE ~ new_allocation) )# calculate remaining tokens
remaining_tokens = available_tokens$available_stake - sum(synced_subgraphs$new_allocation,na.rm=T)
# now sort by best deals, and increment the top one by 100
synced_subgraphs %<>% arrange(desc(rewards_proportion))
# calculate new allocations - actual calculation -----------------------------------------------
data = synced_subgraphs
# Sort the data by rewards_proportion in descending order, but keep all rows
data = data %>%
arrange(desc(rewards_proportion)) %>%
select(deployment, signalled_tokens, total_allocated_tokens, rewards_proportion, queries_per_indexer, new_allocation)
# Calculate initial remaining tokens
remaining_tokens = available_tokens$available_stake - sum(data$new_allocation, na.rm=TRUE)
# Ensure remaining_tokens is not negative
remaining_tokens = max(remaining_tokens, 0)
# Function to calculate potential rewards_proportion
calculate_rewards_proportion = function(row, additional_allocation) {
(row$signalled_tokens) / (row$total_allocated_tokens + row$new_allocation + additional_allocation)
}
# Check if data is empty
if (nrow(data) == 0) {
print("Error: data is empty. Skipping allocation loop.")
} else {
while (remaining_tokens >= 100) {
# Print remaining tokens at the start of each iteration
# print(paste("Remaining tokens:", remaining_tokens))
# Calculate potential rewards_proportion for each row if we add 100 tokens
data$potential_rewards = mapply(calculate_rewards_proportion, split(data, 1:nrow(data)), 100)
# Find rows that haven't reached max_allocation
eligible_rows = which(data$new_allocation + 100 <= max_allocation)
# If no eligible rows, break the loop
if (length(eligible_rows) == 0) {
print("No eligible rows for allocation. Breaking loop.")
break
}
# Find the best eligible row
best_row = eligible_rows[which.max(data$potential_rewards[eligible_rows])]
# Allocate 100 tokens to the best row
data$new_allocation[best_row] = data$new_allocation[best_row] + 100
data$total_allocated_tokens[best_row] = data$total_allocated_tokens[best_row] + 100
remaining_tokens = remaining_tokens - 100
# Recalculate rewards_proportion for the updated row
data$rewards_proportion[best_row] = data$signalled_tokens[best_row] / data$total_allocated_tokens[best_row]
# Print information about the allocation
# print(paste("Allocated 100 tokens to row", best_row, ". New allocation:", data$new_allocation[best_row]))
}
}
# Print final allocation summary
print(paste("Total rows:", nrow(data)))## [1] "Total rows: 166"## [1] "Rows with non-zero allocation: 166"## [1] "Total allocated: 974200"## [1] "Remaining tokens: 71.3133459367091"# Ensure that synced_subgraphs is updated with the new allocations
synced_subgraphs %<>%
left_join(data %>% select(deployment, new_allocation), by = "deployment") %>%
mutate(new_allocation = coalesce(new_allocation.y, new_allocation.x)) %>%
select(-new_allocation.x, -new_allocation.y)# Final sorted dataset
final_allocations_data = data %>% arrange(desc(new_allocation)) %>% filter(new_allocation > 0)
# show final data
print(final_allocations_data)## deployment signalled_tokens total_allocated_tokens rewards_proportion
## 1 QmS1nPRvYghS9UBrqFWP3W7XNnrrJCk9PR9CwiP82fiUGY 6400.511933 1701597.0 0.003761473
## 2 QmVFGoBvTa2YWE5QCDXFg1EeaYHKvds9voYQGd2PWRPdrZ 4901.509931 1399898.0 0.003501334
## 3 QmQkayp7TGrYTCbZ5tAz1NNCv2rRfhiFbCacd2yFrtmMZW 2852.191752 789852.0 0.003611046
## 4 QmXQw8YADkc9LtcYxBCZq1NHJFNt6whZZn7Q45XEbsTttD 2911.535908 812053.0 0.003585401
## 5 QmdGmCh3dL4McHWLzkoLeoHUZZP9c6WcJpwhf7FRCoFxqN 2998.027919 838068.0 0.003577309
## 6 QmYAafEPam85rVLcDRZqGXUmwrfj34GfZ91WK751LsphrC 3175.209655 902079.0 0.003519880
## 7 QmSDPnHzyW8yfnuhB423ssVY5r4bQrr5C1rXT8qMroNgmv 1642.879488 456417.0 0.003599514
## 8 QmcK5HmdqJjhJh18g8cTog2FYP7497T2nz25ESaWdyXk1Z 2971.067218 855360.8 0.003473467
## 9 Qmduy6o7VkWqJRgBqHUVVuPnowT6kAqWJmQWo5WecgKsV6 3433.186067 994298.0 0.003452874
## 10 QmYk6JtWHXCaRbLkLxFJ5A7oPkKAJ3k61efUxDk5SgTur7 1981.077730 561289.9 0.003529509
## 11 QmbnwSqo4RSDUuP7Kf5WAtj4DLCWFDhyhTRPM2drthaGVQ 4919.804078 1442542.0 0.003410510
## 12 QmQYz9UE3uNhweSS4WQv9gW4HzYMSZZtE6tPuVRsyWLAsz 1980.000000 565199.0 0.003503191
## 13 QmRg3LG1pCZB9xWFS6z2iAwDwgSRta7JjCFTfdyVvHg9w1 257.694367 52912.0 0.004870244
## 14 QmNVHQWAUsrjq83SQCD7R8M4HAUyVvsrPcwHisPTfGrw1Z 932.066195 255776.0 0.003644072
## 15 QmSMf99YyUBJuSf2JroPDHDpNuR54esqq3emudg9vaoWKP 3235.891720 944815.7 0.003424892
## 16 QmQJDsmwXbFYmS2z9kqeJq4xdKzXT9DX9ZijBiR9Pd2nDA 998.759691 276300.0 0.003614765
## 17 Qmer3SqyLUB4BRzvpCWeDLmKQi3Lyh4cBojkBBEFpgrTTC 505.094416 129998.0 0.003885401
## 18 QmRuPq9vmTwDPEQvUaoMGvB3zEPc5S3J1wuJPoW5WMTuVL 516.105783 135608.0 0.003805865
## 19 QmYNYWiVGHkRFjYMULxyECVgsaYfXDibEhjBx9sWTtsz9c 2492.870031 726737.0 0.003430223
## 20 QmWRpp5fQJLvq83ziAid4pKo6DKUWdFvF5F9o9EZnKuPvP 1462.758657 420873.0 0.003475535
## 21 QmW8NKJZoYsu8v5KuknpSHdANJ6e97fWy1S9D5qMTPiP5q 1980.094654 579269.0 0.003418264
## 22 QmXtiD3cPJ51x4cyzCy51Cw8f8V64AwoejRWZyR8EtaGyo 2239.776062 657227.0 0.003407919
## 23 QmYodpkEm88nPwAi1QBnS8UVnidGGQTP3cmpB4Fp1y4Aex 3036.334127 896155.0 0.003388180
## 24 Qme5nGiCCDJcDtA5xoJ4iPAtjQgBfLekqRvxXesKCiH8XX 1593.844328 466618.0 0.003415737
## 25 QmVeh3KUMBRNTTTZDipWFEdPrxnnnHz3yzyugRvJJwzXrY 97.029900 19500.0 0.004975892
## 26 QmaoWjQg4gFLV6LH3R9Db7cuppGMNjB4MG6V2gXzqfJWj7 144.336969 34300.0 0.004208075
## 27 Qmb1kpm8RzXRQUD8gBHSuPqd8HAkcQds577cauahwejDp9 53.216986 7500.0 0.007095598
## 28 QmaE9BZUMPpc9mcJPVbG9xnz6xWKDVKJeUyndcLWCi1nKr 83.400506 17000.0 0.004905912
## 29 QmaBwqJfMSksDTGNSGg8HSPwHdsFEq6HMSCAcCBJMrN3Pw 267.848924 72222.0 0.003708689
## 30 QmQTGTovKTt3pni5iRyeWKYkUM2sttEahfDd5yhwqqiBkW 326.791728 90995.0 0.003591315
## 31 QmVHVUTkiTEdF7SijmwvjaGYcPYgwwBBnPd6f177bqFuhd 573.632192 165113.0 0.003474179
## 32 QmQsTaSDMfskRNLcWEzaxufUj1wTxL3MR9af6jtomsQMvr 72.289406 15800.0 0.004575279
## 33 QmcMk21Jdeng7SWv8yqhskhKbykqgH12vE64cnNhzSbXJ8 2046.994385 606113.5 0.003377246
## 34 QmZzoueJuv3dWLFgGSCoK5A1UomR61BhhhbtD9nPT6i2cw 49.500000 9800.0 0.005051020
## 35 QmTiCYux4Jxmn6ur2g7w7R9rUjpftQdRdantexSyzR5peX 49.500000 9800.0 0.005051020
## 36 QmfW5ePHUCrQ51fCcbJUvtKd7NRPeHei16cR8m1taHku8U 49.500000 9800.0 0.005051020
## 37 Qmck1XDhZcCYCsdKYXy2DS7CS3kQfEHT67NVan5cfCmLC1 27.432854 3600.0 0.007620237
## 38 QmbrFgsMRiVSFLdpT5NveyioE1L6P5RCgy5eNYQvufhuLp 39.813206 8400.0 0.004739667
## 39 QmZ9woCuBdvfqn8MSQSe22ivuYFXw1EW5EgSeVd2tETTmy 97.055966 25675.0 0.003780174
## 40 QmbcPkYbBDageNbGCvzGkAggLrmRygabbTKbbvknkoTeuW 396.000871 115499.0 0.003428609
## 41 QmcQe363orcX5u5DtLvjGrjwfCR89vfrA9YLjHWZc3zutD 18.864201 2800.0 0.006737215
## 42 QmaRd3T8BTfPMNMrxo9uehkZFuHeqavLxUhAXTnQ3xPbGj 68.329451 17640.0 0.003873552
## 43 QmPiXvLKgVwTngiFGfi6p4sA75WYsizgbbdNnGw6nyhNMX 58.806000 15400.0 0.003818571
## 44 QmRAbgoZ2mBpxqj4Z32KFaso8rsDhdm8KcwEQhWMzD8bTN 13.878682 2000.0 0.006939341
## 45 QmcN5d7N4Xe6tL9pW9U71jzo9sPSuioaJeCqbbAC1PhWQD 20.207914 4000.0 0.005051979
## 46 Qma9bvmT39fCkG5woFkrXLebPUbbXGSBcXQD9Z3vArJyso 11.897579 1700.0 0.006998576
## 47 Qmap5Ycg96Cb4wikiraf4hQTRMRi2dERKVff9RPruaKnrd 11.892536 1700.0 0.006995609
## 48 QmSxmGgUGwYskjkbzQZEjLC8jHbd1hjdcV8ifAiQRtDwZL 11.898762 1700.0 0.006999272
## 49 Qmc1mFtNdvykyysPZd8sAMz3tmvyeRWMDxpmggukTx7g1x 11.892538 1700.0 0.006995611
## 50 QmPjeesdXSYBstNqJMDjqkpZP1CLtotR2y7Lom75JhBuG9 24.837083 5700.0 0.004357383
## 51 QmXvh2JpDWbxC3hbhzU1UMYYwWCozQobhvpaTPq5HongSP 68.919595 18877.0 0.003650982
## 52 QmVf3FcBasTsmATxekgL1QQKsK72CR9TG8zHwS1tJ5Tx4p 10.902607 1600.0 0.006814129
## 53 QmVEWdQQTJNoURcdefRQm8JEZo7TFtLA1dwkMRrBs2585Z 10.164842 1500.0 0.006776561
## 54 QmdVmkErFM4RxYYTeoq786cnYkR41FmjPTpA7QzD8kfhA2 17.382444 3500.0 0.004966413
## 55 QmTScm43kN2xfdKK9h7nWs3a7c7ypjPjtKJe1NsAsCfnCL 9.850500 1400.0 0.007036071
## 56 QmWZrJghWFFqFaYteYmoFoBaMeancixDhU1qe2ZpSQ9Hir 9.571647 1400.0 0.006836891
## 57 QmeWYQm1r39iZdKTzJYzNYHKmfNSWYEdq8cprPpfz44n88 18.887996 4300.0 0.004392557
## 58 QmZ119nJYGVhsSSP8cCeBY1YpwoQCKBFhfvoxAy7fWs3Qi 65.347475 18217.0 0.003587170
## 59 QmeHZcGmj7wrJMHRrPVDGiVaprs7t21n1jjeUHhPUeMRcA 3.401435 0.0 Inf
## 60 QmbGxMtiEqy3j6DaPDABApKm9jKQZJQ6oNkbz1UtTDJxmR 2.687366 0.0 Inf
## 61 Qmb27RY3RqP98UMKbTgScf6F7hhokfMuS9fV7VAtPiZHwF 8696.140420 2625913.6 0.003311663
## 62 QmUS8ekFtGby8TQhxt7i3RoQySb1QVtKW4VBU2CG2pS9Eh 911.920913 276362.0 0.003299733
## 63 Qmaa4sr6PG4agPMTZfpRnALEhVJ5argjQ41UJ5pELnwU7Z 1377.840947 417834.0 0.003297580
## 64 Qmdv8zRyxPC7cmi5fpTdcViptimbCwaHVdb71sXPdWzUhL 780.343047 240981.0 0.003238193
## 65 QmSrAHvu1fmiF3D4nraQSqfg8qZEWEPGhGicAY2hMrR8Ld 2938.655186 914224.0 0.003214371
## 66 QmcQSBBPpJgDcYrKyGy6oGP9BN7FcczRv32t1cfKbtWuRU 397.381610 124878.0 0.003182159
## 67 QmQamfGnZ1bwt3Y1EzpSfxSG1HsdwpJfgpJGqdMMoPheFz 3191.220538 1009480.0 0.003161252
## 68 QmdorsAVanFXUyFQsfKaTJ6YykhH5PpJc9TG4mSBppPfsU 5574.408155 1798863.0 0.003098851
## 69 Qmc4J3epkBZggHMA3dTSX5TPi4Eq2bn4JtZM17VDihMQiV 3246.512401 1065364.0 0.003047327
## 70 QmWXhLkz6fRJwLyFmgBKVu2NyMD6MqtGhcrt8bNcm1xpuU 6662.607364 2198541.4 0.003030467
## 71 QmccY1R6zSqgkVN37gg3TXGCAoUr1DMhgBg4oPCyrSTcGA 19105.836186 6369520.7 0.002999572
## 72 QmQBU2EcWk8X6KuTczQnqtPFyi49XKfvSQSZprn4RWhBZ5 12273.645516 4093716.3 0.002998167
## 73 QmXoMwNirjRgtJkzGt2PCwQomRqkopTxmB9E5MXz3gGxPD 1040.490569 347792.0 0.002991704
## 74 QmbzgPPc7pHwRetjTjGY7tfNG7sfrbkDpbhYFewtisZpvc 6214.021429 2088636.0 0.002975158
## 75 QmQoJMZT4bLLUNvf9Z15VNub6Wk1oq6VcMm34omrrVZevs 1109.014464 401000.0 0.002765622
## 76 QmUzRg2HHMpbgf6Q4VHKNDbtBEJnyp5JWCh2gUX9AV6jXv 54553.905379 21163181.5 0.002577774
## 77 QmYXL6XeXyGC2DCnoQ45ApG68pi8irCZdRdtFx69FetRDd 13939.861643 6605784.0 0.002110251
## 78 QmXZiV6S13ha6QXq4dmaM3TB4CHcDxBMvGexSNu9Kc28EH 63230.063377 38527277.9 0.001641177
## 79 QmYWvmm6rxvAk8E3cA6iXPhC6ETBLJFuEw8maYJ7YV9ATx 20458.764706 15394111.3 0.001328999
## 80 QmVUMSVtJ4uAfUBBcgYJ9Ed43j27TZirZd7gzv6cUVqT6x 0.000000 0.0 0.000000000
## 81 QmQfH6zEaoHns9d3jNwko8QXmb8xVofQKPdCLop6qKMUnn 5.900000 800.0 0.007375000
## 82 QmXUTLBibdxWtk37dxJLcchSZfRz7FxKHdqrQwc6y5zwas 5.880600 800.0 0.007350750
## 83 QmNeyrYWm2HgmJ1EUToNfacWUaiDmTnV32EJa9TvndVg9f 5.940000 800.0 0.007425000
## 84 QmZPVq8VQWGp6K8WMmExuLEEnekzhG39tJttymoY4CZoAe 117.426439 34126.0 0.003440967
## 85 QmQSNjw39ij4nmjNmpsC6t3fkBvjdfMujK52bkRHExuyM6 4.962533 700.0 0.007089332
## 86 QmcBxAXivw8bkNAhqavTzjEtbH8KSeS8NaSUiPU2fSbqWQ 4.395600 600.0 0.007326000
## 87 QmcZaxZhpJ3HUKxtV1HD29TFf52GprC6HRbJkC8w6soizb 3.000000 400.0 0.007500000
## 88 QmeHJ8Wyk7HpAtFLSNNraVkoiqv78MheDJfLpbdGBb8U2L 3.000000 400.0 0.007500000
## 89 QmT4t8qY58x1M6wyGrY4DmMsxa6oEYWurP1TULL1Ca3GTc 2.970000 400.0 0.007425000
## 90 QmfQWmNKDBuZ9xrhk9oe4X9dB8svZSdJAeQEdva4KbaK25 1676.640783 500853.0 0.003347571
## 91 QmWMLVUQCzsqvQjjaAncpRdkjSVnRBJyZ92a3YAUj9Ynm8 2.000000 200.0 0.010000000
## 92 QmZhm7MB9vuPkBeH5yNziz7jsUBZ8eHcAZYDo1n3EXjt9R 1.980000 200.0 0.009900000
## 93 QmcFx1aE7VhWXkQhcZyrzfm8AGkSzSWeid2FjTEkYBfKou 1.940612 300.0 0.006468708
## 94 QmPrUvv9vfDrBoZ2rU6CGeu23FijhHtnKiVFAvarVRHzYx 1.000000 100.0 0.010000000
## 95 QmTEQP9HPHsgQiKdNREVHS7F4waxEwCeq32eTU5hCRXgN4 1.000000 100.0 0.010000000
## 96 QmV4wyo47CoTejAVW6Cw4EVVc4pL4CWNmFWHwrwTsJrjiK 1.000000 100.0 0.010000000
## 97 QmVa4x9Jqhq2b3QbUTfTgeqCvVZtvuZva7CSg8fnKiNT5A 1.000000 100.0 0.010000000
## 98 QmPB1fZxWhgMA9u6K7TNzqjU287EtwuPx8nyxAFSLikgRi 1.000000 100.0 0.010000000
## 99 QmfNxUwbA6Sx1HoqTaFmLNNhcyjm7QG1qjZu5U7CBx9cdi 1.000000 100.0 0.010000000
## 100 QmatbdjawELyy69kyuG7TC8RKebsdgMoRpwX5ZYy9rURbC 1.000000 100.0 0.010000000
## 101 QmcRTvnRqeyQQeKQEuGAckhvCd431LmqxH8oBrCUHzPcRM 1.000000 100.0 0.010000000
## 102 QmWdUm7HxFFXysSLGvFB1zjaSeYR8SPiLDo2M4gopdHajK 1.000000 100.0 0.010000000
## 103 QmWiGJfHJq3cdPzJrtoiraAJ4CymF5yTW2JZM6pMqGtifd 1.000000 100.0 0.010000000
## 104 QmVagvbwFHWGEBUxhXW1DZWFNvvwYAcUvbJGVorGXetsc7 1.000000 100.0 0.010000000
## 105 QmfE7XHYSeZ6ptESATYb1FtW4sqtWxiVCjXTbPY98ajqBe 1.000000 100.0 0.010000000
## 106 Qmav5jabEyBRv2botzgLK717DJQWokk6kW3AeXxCkPWuSY 1.000000 100.0 0.010000000
## 107 QmYEuY1JBNQDad8W2oPxdQrA58TfD7trVPzkhAjU223baS 1.000000 100.0 0.010000000
## 108 QmS7wExrveyxpN5g6sfykDUkVHX7oGqvMr8Mw82SueXU8S 1.000000 100.0 0.010000000
## 109 QmbK8eiivKro8XT9xALjQSbDtcdTBPVYzZeC29gUua7P7F 1.000000 100.0 0.010000000
## 110 QmZM8HcNZRZDNTKf4wGZmiSJRX5EQNaZcHrG2BpjqDLkUE 1.000000 100.0 0.010000000
## 111 QmaBvS459yzfu5ykA9eL6S8t1J8PeCm8n3112DVWqSNis5 1.000000 100.0 0.010000000
## 112 QmT8Y6WqcTD6iR6DbTzfwQUiar5FtuZnqJhT3t28dp4SXD 1.000000 100.0 0.010000000
## 113 QmaJcXuvGW3GST8UfjTHSXSpmJ4YupCXfyYq6K2L99FX1w 1.000000 100.0 0.010000000
## 114 QmS9GuSvYWfsh1vJckTt6DSwAnnPxQ8XqWoz6tF6Zh4NLi 1.000000 100.0 0.010000000
## 115 QmXX9JNqpsmph2GdgJNHFB1Xm9JSAni3QZZ96vfngXU4KE 1.000000 100.0 0.010000000
## 116 QmXYNUvUc9CriaaCfkevhjG8389GqYXPEM7S6zQTq1dB8P 1.000000 100.0 0.010000000
## 117 QmNs1YDpRPdHFcXdyZ9nwDQAx74hwuWDyULE74rejd4THP 1.000000 100.0 0.010000000
## 118 QmSJpz3ozq7eziF8qCWcSSLobWbcKT8NjwSn79ErFArkFY 1.000000 100.0 0.010000000
## 119 QmfTYPHrWaYkaFzwCwmXXshc3Vb7pp77uiqB7XmBb7g14b 1.000000 100.0 0.010000000
## 120 QmaB28b3BMpEnPtqJyuAQNuCzkGgWPXbaYrH7pjDJR7NYL 1.000000 100.0 0.010000000
## 121 QmNi1Vyaz6bR6ag3NFBgqWabaQkE2zELvEpB8Xi3qFK9YF 1.000000 100.0 0.010000000
## 122 QmVgdHuPrJiWbHDez2M8D6k3WrJ7FN1PK5KHAZt5c2dJE8 1.000000 100.0 0.010000000
## 123 QmeZ9q66wq9nWJjrsadQ3YExLsVoMZqA79zPCtXpCFutX6 1.000000 100.0 0.010000000
## 124 QmbNf8kZMDURSwBrsTfoqn3QfowCx2gEhCBFE3qKTTGZAG 1.000000 100.0 0.010000000
## 125 QmUjTw5kC7RoTwNuLoGtPsyfRQBioosWDYZCE81RR5T95R 1.000000 100.0 0.010000000
## 126 QmdUknu8tyvH1BAE1X2rshXNDBPToYtQ8JypEKTxxcdGem 1.000000 100.0 0.010000000
## 127 QmSL65DYNfaaabj4tVeTnAzinpgZsDvEUsTsEu79YykxjW 1.000000 100.0 0.010000000
## 128 QmSfKsoBUHcezd6uhhftvFAjLQm1JvbJLRPPGHRvzTYwna 1.000000 100.0 0.010000000
## 129 Qme4i64hYrHrAgwuHXfnMhkyeYRkT89uXDuvHQMxX2woeR 1.000000 100.0 0.010000000
## 130 QmbWhGfCrewoQvwJ7GSvAm51AX8Z3rb8q3fsJNvAFB9svz 1.000000 100.0 0.010000000
## 131 QmdiykT6LaGCiqPwrpZMsYzXh2PExBbnR3fcLj15q5cdXd 1.000000 100.0 0.010000000
## 132 QmfUgbmMzMtFZ1ZEjuF9dBKCaFybHj2VkSozNBAT2A6QLZ 1.000000 100.0 0.010000000
## 133 QmWjKBaLENbsi2BPzUxpdiX7FUmw1eZqjEfLNv83RNb6YD 1.000000 100.0 0.010000000
## 134 Qmej11EGGzNGfbnEKbda3tHJogv9fwt2Rk3GRWNd8kY3Uq 1.000000 100.0 0.010000000
## 135 QmSj3cbVeNzXywVHQ1Ary5spgsa6LyrWcnhyRyLBPb4GKz 1.000000 100.0 0.010000000
## 136 QmSdc5FFbLzF436KEqYjCn3BLL5HN69ASNucTFnFqtGUUn 1.000000 100.0 0.010000000
## 137 QmZ3TUhnG2cJxniWhy7zFk7vZCVnmUZagWcvURuhGBp3Nd 1.000000 100.0 0.010000000
## 138 QmZqKd3ZvqwWcLsydUdQoW3gEJS9KthEEEqBVKC9qkLXbe 1.000000 100.0 0.010000000
## 139 QmSfYVdY2taCQ7DtLYXo19CkCdNWc8HN1oUuVjEJhoKqhz 1.000000 100.0 0.010000000
## 140 QmdX1F96DH26zMfyCnp8uVNbbJUJiq7UAjXeVvm2aDvwwr 1.000000 100.0 0.010000000
## 141 QmbPUyAyzyVVFpaJCS7T9g6imVwp9LRJLP9ZWumwUjQeKj 1.000000 100.0 0.010000000
## 142 Qmb4YEj9qpoZd8iLVLWPdfVMsG3o5qBcFxZHXucGrUnd2w 1.000000 100.0 0.010000000
## queries_per_indexer new_allocation potential_rewards
## 1 461263.615385 108300 0.003536200
## 2 154.307692 65500 0.003344604
## 3 757.833333 63000 0.003343907
## 4 324.750000 58500 0.003344083
## 5 67365.083333 58300 0.003344267
## 6 171028.400000 47200 0.003344512
## 7 236515.625000 34800 0.003343828
## 8 211.214286 32900 0.003344438
## 9 4346.272727 32100 0.003344562
## 10 5.714286 31100 0.003343648
## 11 91882.333333 28400 0.003344435
## 12 3086.333333 26800 0.003344035
## 13 205126.200000 24100 0.003341819
## 14 7.333333 22800 0.003344623
## 15 177458.384615 22600 0.003344537
## 16 59587.500000 22400 0.003342569
## 17 320970.500000 21000 0.003342827
## 18 113576.600000 18800 0.003340318
## 19 210202.076923 18600 0.003344173
## 20 190838.444444 16500 0.003343655
## 21 266.571429 12700 0.003344365
## 22 622007.700000 12500 0.003343813
## 23 111945.555556 11600 0.003344514
## 24 204660.388889 10000 0.003343369
## 25 4722.500000 9600 0.003322942
## 26 159565.400000 8800 0.003341134
## 27 317954.000000 8500 0.003305403
## 28 111554.000000 8000 0.003322729
## 29 58556.181818 7800 0.003343013
## 30 39064.600000 6700 0.003341600
## 31 180887.727273 6400 0.003342592
## 32 62.000000 5900 0.003316028
## 33 54501.500000 5900 0.003344142
## 34 355.500000 4900 0.003344595
## 35 38.000000 4900 0.003344595
## 36 1118.500000 4900 0.003344595
## 37 177369.000000 4600 0.003305163
## 38 38.000000 3500 0.003317767
## 39 2916.000000 3400 0.003326683
## 40 9.222222 3000 0.003344630
## 41 333888.500000 2800 0.003309509
## 42 34.500000 2700 0.003342928
## 43 106.500000 2200 0.003322373
## 44 81.000000 2100 0.003304448
## 45 34.000000 2100 0.003259341
## 46 71.000000 1800 0.003304883
## 47 74.000000 1800 0.003303482
## 48 80.000000 1800 0.003305212
## 49 67.000000 1800 0.003303483
## 50 6083.000000 1800 0.003268037
## 51 38.000000 1800 0.003317110
## 52 79.000000 1700 0.003206649
## 53 81.000000 1600 0.003176513
## 54 32.500000 1600 0.003342778
## 55 1806.000000 1500 0.003283500
## 56 78.000000 1500 0.003190549
## 57 44134.666667 1300 0.003313683
## 58 37.333333 1300 0.003331166
## 59 284414.000000 1000 0.003092214
## 60 313572.000000 1000 0.002443060
## 61 856359.263158 1000 0.003310276
## 62 296867.666667 1000 0.003286652
## 63 244523.750000 1000 0.003288921
## 64 168738.375000 1000 0.003223479
## 65 134057.428571 1000 0.003210508
## 66 118133.666667 1000 0.003154373
## 67 269878.100000 1000 0.003157811
## 68 220316.785714 1000 0.003096957
## 69 219546.909091 1000 0.003044184
## 70 558612.428571 1000 0.003028952
## 71 419309.555556 1000 0.002999054
## 72 803563.812500 1000 0.002997362
## 73 469802.333333 1000 0.002982271
## 74 274619.090909 1000 0.002973592
## 75 219340.000000 1000 0.002758056
## 76 4932102.518519 1000 0.002577640
## 77 286967.375000 1000 0.002109900
## 78 1012608.941176 1000 0.001641130
## 79 261210.800000 1000 0.001328904
## 80 Inf 1000 0.000000000
## 81 73.000000 900 0.003277778
## 82 73.000000 900 0.003267000
## 83 79.000000 900 0.003300000
## 84 3036.111111 900 0.003343006
## 85 77.000000 800 0.003101583
## 86 68.000000 700 0.003139714
## 87 192.000000 500 0.003000000
## 88 198.000000 500 0.003000000
## 89 74.000000 500 0.002970000
## 90 3305.000000 500 0.003343565
## 91 148.000000 300 0.003333333
## 92 75.000000 300 0.003300000
## 93 34.000000 300 0.002772303
## 94 75.000000 200 0.002500000
## 95 74.000000 200 0.002500000
## 96 75.000000 200 0.002500000
## 97 74.000000 200 0.002500000
## 98 73.000000 200 0.002500000
## 99 68.000000 200 0.002500000
## 100 68.000000 200 0.002500000
## 101 69.000000 200 0.002500000
## 102 74.000000 200 0.002500000
## 103 74.000000 200 0.002500000
## 104 74.000000 200 0.002500000
## 105 69.000000 200 0.002500000
## 106 502.000000 200 0.002500000
## 107 75.000000 200 0.002500000
## 108 4847.000000 200 0.002500000
## 109 71.000000 200 0.002500000
## 110 87.000000 200 0.002500000
## 111 69.000000 200 0.002500000
## 112 79.000000 200 0.002500000
## 113 70.000000 200 0.002500000
## 114 74.000000 200 0.002500000
## 115 72.000000 200 0.002500000
## 116 72.000000 200 0.002500000
## 117 103.000000 200 0.002500000
## 118 79.000000 200 0.002500000
## 119 68.000000 200 0.002500000
## 120 70.000000 200 0.002500000
## 121 75.000000 200 0.002500000
## 122 74.000000 200 0.002500000
## 123 88.000000 200 0.002500000
## 124 70.000000 200 0.002500000
## 125 76.000000 200 0.002500000
## 126 68.000000 200 0.002500000
## 127 74.000000 200 0.002500000
## 128 74.000000 200 0.002500000
## 129 72.000000 200 0.002500000
## 130 73.000000 200 0.002500000
## 131 68.000000 200 0.002500000
## 132 68.000000 200 0.002500000
## 133 74.000000 200 0.002500000
## 134 67.000000 200 0.002500000
## 135 75.000000 200 0.002500000
## 136 74.000000 200 0.002500000
## 137 74.000000 200 0.002500000
## 138 74.000000 200 0.002500000
## 139 74.000000 200 0.002500000
## 140 66.000000 200 0.002500000
## 141 75.000000 200 0.002500000
## 142 68.000000 200 0.002500000
## [ reached 'max' / getOption("max.print") -- omitted 24 rows ]