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fetch.cc
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// Copyright 2020 Redpanda Data, Inc.
//
// Use of this software is governed by the Business Source License
// included in the file licenses/BSL.md
//
// As of the Change Date specified in that file, in accordance with
// the Business Source License, use of this software will be governed
// by the Apache License, Version 2.0
#include "kafka/server/handlers/fetch.h"
#include "cluster/metadata_cache.h"
#include "cluster/partition_manager.h"
#include "cluster/shard_table.h"
#include "config/configuration.h"
#include "kafka/protocol/batch_consumer.h"
#include "kafka/protocol/errors.h"
#include "kafka/protocol/fetch.h"
#include "kafka/server/fetch_session.h"
#include "kafka/server/handlers/details/leader_epoch.h"
#include "kafka/server/handlers/fetch/fetch_plan_executor.h"
#include "kafka/server/handlers/fetch/fetch_planner.h"
#include "kafka/server/materialized_partition.h"
#include "kafka/server/partition_proxy.h"
#include "kafka/server/replicated_partition.h"
#include "likely.h"
#include "model/fundamental.h"
#include "model/namespace.h"
#include "model/record_utils.h"
#include "model/timeout_clock.h"
#include "random/generators.h"
#include "resource_mgmt/io_priority.h"
#include "storage/parser_utils.h"
#include "utils/to_string.h"
#include <seastar/core/do_with.hh>
#include <seastar/core/future.hh>
#include <seastar/core/scheduling.hh>
#include <seastar/core/sleep.hh>
#include <seastar/core/thread.hh>
#include <seastar/core/with_scheduling_group.hh>
#include <seastar/util/log.hh>
#include <boost/range/irange.hpp>
#include <fmt/ostream.h>
#include <chrono>
#include <string_view>
namespace kafka {
static constexpr std::chrono::milliseconds default_fetch_timeout = 5s;
/**
* Make a partition response error.
*/
static fetch_response::partition_response
make_partition_response_error(model::partition_id p_id, error_code error) {
return fetch_response::partition_response{
.partition_index = p_id,
.error_code = error,
.high_watermark = model::offset(-1),
.last_stable_offset = model::offset(-1),
.records = batch_reader(),
};
}
/**
* Low-level handler for reading from an ntp. Runs on ntp's home core.
*/
static ss::future<read_result> read_from_partition(
kafka::partition_proxy part,
fetch_config config,
bool foreign_read,
std::optional<model::timeout_clock::time_point> deadline) {
auto lso = part.last_stable_offset();
if (unlikely(!lso)) {
co_return read_result(lso.error());
}
auto hw = part.high_watermark();
auto start_o = part.start_offset();
// if we have no data read, return fast
if (
hw < config.start_offset || config.skip_read
|| config.start_offset > config.max_offset) {
co_return read_result(start_o, hw, lso.value());
}
storage::log_reader_config reader_config(
config.start_offset,
config.max_offset,
0,
config.max_bytes,
kafka_read_priority(),
std::nullopt,
std::nullopt,
std::nullopt);
reader_config.strict_max_bytes = config.strict_max_bytes;
auto rdr = co_await part.make_reader(reader_config);
std::exception_ptr e;
std::unique_ptr<iobuf> data;
std::vector<cluster::rm_stm::tx_range> aborted_transactions;
try {
auto result = co_await rdr.reader.consume(
kafka_batch_serializer(), deadline ? *deadline : model::no_timeout);
data = std::make_unique<iobuf>(std::move(result.data));
part.probe().add_records_fetched(result.record_count);
part.probe().add_bytes_fetched(data->size_bytes());
if (result.first_tx_batch_offset && result.record_count > 0) {
// Reader should live at least until this point to hold on to the
// segment locks so that prefix truncation doesn't happen.
aborted_transactions = co_await part.aborted_transactions(
result.first_tx_batch_offset.value(),
result.last_offset,
std::move(rdr.ot_state));
}
} catch (...) {
e = std::current_exception();
}
co_await std::move(rdr.reader).release()->finally();
if (e) {
std::rethrow_exception(e);
}
if (foreign_read) {
co_return read_result(
ss::make_foreign<read_result::data_t>(std::move(data)),
start_o,
hw,
lso.value(),
std::move(aborted_transactions));
}
co_return read_result(
std::move(data),
start_o,
hw,
lso.value(),
std::move(aborted_transactions));
}
/**
* Entry point for reading from an ntp. This is executed on NTP home core and
* build error responses if anything goes wrong.
*/
static ss::future<read_result> do_read_from_ntp(
cluster::partition_manager& cluster_pm,
coproc::partition_manager& coproc_pm,
ntp_fetch_config ntp_config,
bool foreign_read,
std::optional<model::timeout_clock::time_point> deadline) {
/*
* lookup the ntp's partition
*/
auto kafka_partition = make_partition_proxy(
ntp_config.ntp(), cluster_pm, coproc_pm);
if (unlikely(!kafka_partition)) {
co_return read_result(error_code::unknown_topic_or_partition);
}
if (unlikely(!kafka_partition->is_leader())) {
co_return read_result(error_code::not_leader_for_partition);
}
/**
* validate leader epoch. for more details see KIP-320
*/
auto leader_epoch_err = details::check_leader_epoch(
ntp_config.cfg.current_leader_epoch, *kafka_partition);
if (leader_epoch_err != error_code::none) {
co_return read_result(leader_epoch_err);
}
auto offset_ec = co_await kafka_partition->validate_fetch_offset(
ntp_config.cfg.start_offset,
default_fetch_timeout + model::timeout_clock::now());
if (config::shard_local_cfg().enable_transactions.value()) {
if (
ntp_config.cfg.isolation_level
== model::isolation_level::read_committed) {
auto maybe_lso = kafka_partition->last_stable_offset();
if (unlikely(!maybe_lso)) {
// partition is still bootstrapping
co_return read_result(maybe_lso.error());
}
ntp_config.cfg.max_offset = model::prev_offset(maybe_lso.value());
}
}
if (offset_ec != error_code::none) {
vlog(
klog.warn,
"fetch offset out of range for {}, requested offset: {}, "
"partition start offset: {}, high watermark: {}, ec: {}",
ntp_config.ntp(),
ntp_config.cfg.start_offset,
kafka_partition->start_offset(),
kafka_partition->high_watermark(),
offset_ec);
co_return read_result(offset_ec);
}
co_return co_await read_from_partition(
std::move(*kafka_partition), ntp_config.cfg, foreign_read, deadline);
}
static ntp_fetch_config
make_ntp_fetch_config(const model::ntp& ntp, const fetch_config& fetch_cfg) {
return ntp_fetch_config(ntp, fetch_cfg);
}
ss::future<read_result> read_from_ntp(
cluster::partition_manager& cluster_pm,
coproc::partition_manager& coproc_pm,
const model::ntp& ntp,
fetch_config config,
bool foreign_read,
std::optional<model::timeout_clock::time_point> deadline) {
return do_read_from_ntp(
cluster_pm,
coproc_pm,
make_ntp_fetch_config(ntp, config),
foreign_read,
deadline);
}
static void fill_fetch_responses(
op_context& octx,
std::vector<read_result> results,
std::vector<op_context::response_placeholder_ptr> responses,
std::vector<std::unique_ptr<hdr_hist::measurement>> metrics) {
auto range = boost::irange<size_t>(0, results.size());
for (auto idx : range) {
auto& res = results[idx];
auto& resp_it = responses[idx];
auto& metric = metrics[idx];
// error case
if (unlikely(res.error != error_code::none)) {
resp_it->set(
make_partition_response_error(res.partition, res.error));
metric->set_trace(false);
continue;
}
model::ntp ntp(
model::kafka_namespace, resp_it->topic(), resp_it->partition_id());
/**
* Cache fetch metadata
*/
octx.rctx.get_fetch_metadata_cache().insert_or_assign(
std::move(ntp),
res.start_offset,
res.high_watermark,
res.last_stable_offset);
/**
* Over response budget, we will just waste this read, it will cause
* data to be stored in the cache so next read is fast
*/
fetch_response::partition_response resp;
resp.partition_index = res.partition;
resp.error_code = error_code::none;
resp.log_start_offset = res.start_offset;
resp.high_watermark = res.high_watermark;
resp.last_stable_offset = res.last_stable_offset;
/**
* According to KIP-74 we have to return first batch even if it would
* violate max_bytes fetch parameter
*/
if (
res.has_data()
&& (octx.bytes_left >= res.data_size_bytes() || octx.response_size == 0)) {
/**
* set aborted transactions if present
*/
if (!res.aborted_transactions.empty()) {
std::vector<fetch_response::aborted_transaction> aborted;
aborted.reserve(res.aborted_transactions.size());
std::transform(
res.aborted_transactions.begin(),
res.aborted_transactions.end(),
std::back_inserter(aborted),
[](cluster::rm_stm::tx_range range) {
return fetch_response::aborted_transaction{
.producer_id = kafka::producer_id(range.pid.id),
.first_offset = range.first};
});
resp.aborted = std::move(aborted);
}
resp.records = batch_reader(std::move(res).release_data());
} else {
// TODO: add probe to measure how much of read data is discarded
resp.records = batch_reader();
}
resp_it->set(std::move(resp));
metric = nullptr;
}
}
static ss::future<std::vector<read_result>> fetch_ntps_in_parallel(
cluster::partition_manager& cluster_pm,
coproc::partition_manager& coproc_pm,
std::vector<ntp_fetch_config> ntp_fetch_configs,
bool foreign_read,
std::optional<model::timeout_clock::time_point> deadline) {
size_t total_max_bytes = 0;
for (const auto& c : ntp_fetch_configs) {
total_max_bytes += c.cfg.max_bytes;
}
auto max_bytes_per_fetch
= config::shard_local_cfg().kafka_max_bytes_per_fetch();
if (total_max_bytes > max_bytes_per_fetch) {
auto per_partition = max_bytes_per_fetch / ntp_fetch_configs.size();
vlog(
klog.debug,
"Fetch requested very large response ({}), clamping each partition's "
"max_bytes to {} bytes",
total_max_bytes,
per_partition);
for (auto& c : ntp_fetch_configs) {
c.cfg.max_bytes = per_partition;
}
}
auto results = co_await ssx::parallel_transform(
std::move(ntp_fetch_configs),
[&cluster_pm, &coproc_pm, deadline, foreign_read](
const ntp_fetch_config& ntp_cfg) {
auto p_id = ntp_cfg.ntp().tp.partition;
return do_read_from_ntp(
cluster_pm, coproc_pm, ntp_cfg, foreign_read, deadline)
.then([p_id](read_result res) {
res.partition = p_id;
return res;
});
});
size_t total_size = 0;
for (const auto& r : results) {
total_size += r.data_size_bytes();
}
vlog(
klog.trace,
"fetch_ntps_in_parallel: for {} partitions returning {} total bytes",
results.size(),
total_size);
co_return results;
}
/**
* Top-level handler for fetching from single shard. The result is
* unwrapped and any errors from the storage sub-system are translated
* into kafka specific response codes. On failure or success the
* partition response is finalized and placed into its position in the
* response message.
*/
static ss::future<>
handle_shard_fetch(ss::shard_id shard, op_context& octx, shard_fetch fetch) {
// if over budget skip the fetch.
if (octx.bytes_left <= 0) {
return ss::now();
}
// no requests for this shard, do nothing
if (fetch.requests.empty()) {
return ss::now();
}
bool foreign_read = shard != ss::this_shard_id();
// dispatch to remote core
return octx.rctx.partition_manager()
.invoke_on(
shard,
octx.ssg,
[foreign_read,
&octx,
deadline = octx.deadline,
configs = std::move(fetch.requests)](
cluster::partition_manager& mgr) mutable {
return fetch_ntps_in_parallel(
mgr,
octx.rctx.coproc_partition_manager().local(),
std::move(configs),
foreign_read,
deadline);
})
.then([responses = std::move(fetch.responses),
metrics = std::move(fetch.metrics),
&octx](std::vector<read_result> results) mutable {
fill_fetch_responses(
octx, std::move(results), std::move(responses), std::move(metrics));
});
}
class parallel_fetch_plan_executor final : public fetch_plan_executor::impl {
ss::future<> execute_plan(op_context& octx, fetch_plan plan) final {
std::vector<ss::future<>> fetches;
fetches.reserve(ss::smp::count);
// start fetching from random shard to make sure that we fetch data from
// all the partition even if we reach fetch message size limit
const ss::shard_id start_shard_idx = random_generators::get_int(
ss::smp::count - 1);
for (size_t i = 0; i < ss::smp::count; ++i) {
auto shard = (start_shard_idx + i) % ss::smp::count;
fetches.push_back(handle_shard_fetch(
shard, octx, std::move(plan.fetches_per_shard[shard])));
}
return ss::when_all_succeed(fetches.begin(), fetches.end());
}
};
class simple_fetch_planner final : public fetch_planner::impl {
fetch_plan create_plan(op_context& octx) final {
fetch_plan plan(ss::smp::count);
auto resp_it = octx.response_begin();
auto bytes_left_in_plan = octx.bytes_left;
/**
* group fetch requests by shard
*/
octx.for_each_fetch_partition(
[&resp_it, &octx, &plan, &bytes_left_in_plan](
const fetch_session_partition& fp) {
// if this is not an initial fetch we are allowed to skip
// partions that aleready have an error or we have enough data
if (!octx.initial_fetch) {
bool has_enough_data = !resp_it->empty()
&& octx.over_min_bytes();
if (resp_it->has_error() || has_enough_data) {
++resp_it;
return;
}
}
/**
* if not authorized do not include into a plan
*/
if (!octx.rctx.authorized(
security::acl_operation::read, fp.topic)) {
resp_it->set(make_partition_response_error(
fp.partition, error_code::topic_authorization_failed));
++resp_it;
return;
}
auto ntp = model::ntp(
model::kafka_namespace, fp.topic, fp.partition);
// there is given partition in topic metadata, return
// unknown_topic_or_partition error
if (unlikely(!octx.rctx.metadata_cache().contains(ntp))) {
resp_it->set(make_partition_response_error(
fp.partition, error_code::unknown_topic_or_partition));
++resp_it;
return;
}
auto shard = octx.rctx.shards().shard_for(ntp);
if (!shard) {
/**
* no shard is found on current node, but topic exists in
* cluster metadata, this mean that the partition was moved
* but consumer has not updated its metadata yet. we return
* not_leader_for_partition error to force metadata update.
*/
resp_it->set(make_partition_response_error(
fp.partition, error_code::not_leader_for_partition));
++resp_it;
return;
}
auto fetch_md = octx.rctx.get_fetch_metadata_cache().get(ntp);
auto max_bytes = std::min(
bytes_left_in_plan, size_t(fp.max_bytes));
/**
* If offset is greater, assume that fetch will read max_bytes
*/
if (fetch_md && fetch_md->high_watermark > fp.fetch_offset) {
bytes_left_in_plan -= max_bytes;
}
fetch_config config{
.start_offset = fp.fetch_offset,
.max_offset = model::model_limits<model::offset>::max(),
.isolation_level = octx.request.data.isolation_level,
.max_bytes = max_bytes,
.timeout = octx.deadline.value_or(model::no_timeout),
.strict_max_bytes = octx.response_size > 0,
.skip_read = bytes_left_in_plan == 0 && max_bytes == 0,
.current_leader_epoch = fp.current_leader_epoch,
};
plan.fetches_per_shard[*shard].push_back(
make_ntp_fetch_config(ntp, config),
&(*resp_it),
octx.rctx.probe().auto_fetch_measurement());
++resp_it;
});
return plan;
}
};
/**
* Process partition fetch requests.
*
* Each request is handled serially in the order they appear in the request.
* There are a couple reasons why we are not **yet** processing these in
* parallel. First, Kafka expects to some extent that the order of the
* partitions in the request is an implicit priority on which partitions to
* read from. This is closely related to the request budget limits specified
* in terms of maximum bytes and maximum time delay.
*
* Once we start processing requests in parallel we'll have to work through
* various challenges. First, once we dispatch in parallel, we'll need to
* develop heuristics for dealing with the implicit priority order. We'll
* also need to develop techniques and heuristics for dealing with budgets
* since global budgets aren't trivially divisible onto each core when
* partition requests may produce non-uniform amounts of data.
*
* w.r.t. what is needed to parallelize this, there are no data dependencies
* between partition requests within the fetch request, and so they can be
* run fully in parallel. The only dependency that exists is that the
* response must be reassembled such that the responses appear in these
* order as the partitions in the request.
*/
static ss::future<> fetch_topic_partitions(op_context& octx) {
auto planner = make_fetch_planner<simple_fetch_planner>();
auto fetch_plan = planner.create_plan(octx);
fetch_plan_executor executor
= make_fetch_plan_executor<parallel_fetch_plan_executor>();
co_await executor.execute_plan(octx, std::move(fetch_plan));
if (octx.should_stop_fetch()) {
co_return;
}
octx.reset_context();
// debounce next read retry
co_await ss::sleep(std::min(
config::shard_local_cfg().fetch_reads_debounce_timeout(),
octx.request.data.max_wait_ms));
}
template<>
ss::future<response_ptr>
fetch_handler::handle(request_context rctx, ss::smp_service_group ssg) {
return ss::do_with(
std::make_unique<op_context>(std::move(rctx), ssg),
[](std::unique_ptr<op_context>& octx_ptr) {
auto sg
= octx_ptr->rctx.connection()->server().fetch_scheduling_group();
return ss::with_scheduling_group(sg, [&octx_ptr] {
auto& octx = *octx_ptr;
log_request(octx.rctx.header(), octx.request);
// top-level error is used for session-level errors
if (octx.session_ctx.has_error()) {
octx.response.data.error_code = octx.session_ctx.error();
return std::move(octx).send_response();
}
octx.response.data.error_code = error_code::none;
// first fetch, do not wait
return fetch_topic_partitions(octx)
.then([&octx] {
return ss::do_until(
[&octx] { return octx.should_stop_fetch(); },
[&octx] { return fetch_topic_partitions(octx); });
})
.then([&octx] { return std::move(octx).send_response(); });
});
});
}
void op_context::reset_context() { initial_fetch = false; }
// decode request and initialize budgets
op_context::op_context(request_context&& ctx, ss::smp_service_group ssg)
: rctx(std::move(ctx))
, ssg(ssg)
, response_size(0)
, response_error(false) {
/*
* decode request and prepare the inital response
*/
request.decode(rctx.reader(), rctx.header().version);
if (likely(!request.data.topics.empty())) {
response.data.topics.reserve(request.data.topics.size());
}
if (auto delay = request.debounce_delay(); delay) {
deadline = model::timeout_clock::now() + delay.value();
}
/*
* TODO: max size is multifaceted. it needs to be absolute, but also
* integrate with other resource contraints that are dynamic within the
* kafka server itself.
*/
bytes_left = std::min(
config::shard_local_cfg().fetch_max_bytes(),
size_t(request.data.max_bytes));
session_ctx = rctx.fetch_sessions().maybe_get_session(request);
create_response_placeholders();
}
// insert and reserve space for a new topic in the response
void op_context::start_response_topic(const fetch_request::topic& topic) {
auto& p = response.data.topics.emplace_back(
fetchable_topic_response{.name = topic.name});
p.partitions.reserve(topic.fetch_partitions.size());
}
void op_context::start_response_partition(const fetch_request::partition& p) {
response.data.topics.back().partitions.push_back(
fetch_response::partition_response{
.partition_index = p.partition_index,
.error_code = error_code::none,
.high_watermark = model::offset(-1),
.last_stable_offset = model::offset(-1),
.records = batch_reader()});
}
void op_context::create_response_placeholders() {
if (session_ctx.is_sessionless() || session_ctx.is_full_fetch()) {
std::for_each(
request.cbegin(),
request.cend(),
[this](const fetch_request::const_iterator::value_type& v) {
if (v.new_topic) {
start_response_topic(*v.topic);
}
start_response_partition(*v.partition);
});
} else {
model::topic last_topic;
std::for_each(
session_ctx.session()->partitions().cbegin_insertion_order(),
session_ctx.session()->partitions().cend_insertion_order(),
[this, &last_topic](const fetch_session_partition& fp) {
if (last_topic != fp.topic) {
response.data.topics.emplace_back(
fetchable_topic_response{.name = fp.topic});
last_topic = fp.topic;
}
fetch_response::partition_response p{
.partition_index = fp.partition,
.error_code = error_code::none,
.high_watermark = fp.high_watermark,
.last_stable_offset = fp.last_stable_offset,
.records = batch_reader()};
response.data.topics.back().partitions.push_back(std::move(p));
});
}
for (auto it = response.begin(); it != response.end(); ++it) {
auto raw = new response_placeholder(it, this); // NOLINT
iteration_order.push_back(*raw);
}
}
bool update_fetch_partition(
const fetch_response::partition_response& resp,
fetch_session_partition& partition) {
bool include = false;
if (resp.records && resp.records->size_bytes() > 0) {
// Partitions with new data are always included in the response.
include = true;
}
if (partition.high_watermark != resp.high_watermark) {
include = true;
partition.high_watermark = model::offset(resp.high_watermark);
}
if (partition.last_stable_offset != resp.last_stable_offset) {
include = true;
partition.last_stable_offset = model::offset(resp.last_stable_offset);
}
if (include) {
return include;
}
if (resp.error_code != error_code::none) {
// Partitions with errors are always included in the response.
// We also set the cached highWatermark to an invalid offset, -1.
// This ensures that when the error goes away, we re-send the
// partition.
partition.high_watermark = model::offset{-1};
include = true;
}
return include;
}
ss::future<response_ptr> op_context::send_response() && {
// Sessionless fetch
if (session_ctx.is_sessionless()) {
response.data.session_id = invalid_fetch_session_id;
return rctx.respond(std::move(response));
}
// bellow we handle incremental fetches, set response session id
response.data.session_id = session_ctx.session()->id();
if (session_ctx.is_full_fetch()) {
return rctx.respond(std::move(response));
}
fetch_response final_response;
final_response.data.error_code = response.data.error_code;
final_response.data.session_id = response.data.session_id;
/// Account for special internal topic bytes for usage
for (const auto& topic : response.data.topics) {
const bool bytes_to_exclude = std::find(
usage_excluded_topics.cbegin(),
usage_excluded_topics.cend(),
topic.name)
!= usage_excluded_topics.cend();
if (bytes_to_exclude) {
for (const auto& part : topic.partitions) {
if (part.records) {
final_response.internal_topic_bytes
+= part.records->size_bytes();
}
}
}
}
for (auto it = response.begin(true); it != response.end(); ++it) {
if (it->is_new_topic) {
final_response.data.topics.emplace_back(
fetchable_topic_response{.name = it->partition->name});
final_response.data.topics.back().partitions.reserve(
it->partition->partitions.size());
}
fetch_response::partition_response r{
.partition_index = it->partition_response->partition_index,
.error_code = it->partition_response->error_code,
.high_watermark = it->partition_response->high_watermark,
.last_stable_offset = it->partition_response->last_stable_offset,
.log_start_offset = it->partition_response->log_start_offset,
.aborted = std::move(it->partition_response->aborted),
.records = std::move(it->partition_response->records)};
final_response.data.topics.back().partitions.push_back(std::move(r));
}
return rctx.respond(std::move(final_response));
}
op_context::response_placeholder::response_placeholder(
fetch_response::iterator it, op_context* ctx)
: _it(it)
, _ctx(ctx) {}
void op_context::response_placeholder::set(
fetch_response::partition_response&& response) {
vassert(
response.partition_index == _it->partition_response->partition_index,
"Response and current partition ids have to be the same. Current "
"response {}, update {}",
_it->partition_response->partition_index,
response.partition_index);
if (response.error_code != error_code::none) {
_ctx->response_error = true;
}
auto& current_resp_data = _it->partition_response->records;
if (current_resp_data) {
auto sz = current_resp_data->size_bytes();
_ctx->response_size -= sz;
_ctx->bytes_left += sz;
}
if (response.records) {
auto sz = response.records->size_bytes();
_ctx->response_size += sz;
_ctx->bytes_left -= std::min(_ctx->bytes_left, sz);
}
*_it->partition_response = std::move(response);
// if we are not sessionless update session cache
if (!_ctx->session_ctx.is_sessionless()) {
auto& session_partitions = _ctx->session_ctx.session()->partitions();
auto key = model::topic_partition_view(
_it->partition->name, _it->partition_response->partition_index);
if (auto it = session_partitions.find(key);
it != session_partitions.end()) {
auto has_to_be_included = update_fetch_partition(
*_it->partition_response, it->second->partition);
/**
* From KIP-227
*
* In order to solve the starvation problem, the server must
* rotate the order in which it returns partition information.
* The server does this by maintaining a linked list of all
* partitions in the fetch session. When data is returned for a
* partition, that partition is moved to the end of the list.
* This ensures that we eventually return data about all
* partitions for which data is available.
*
*/
if (
_it->partition_response->records
&& _it->partition_response->records->size_bytes() > 0) {
// move both session partition and response placeholder to the
// end of fetch queue
session_partitions.move_to_end(it);
move_to_end();
}
_it->partition_response->has_to_be_included = has_to_be_included;
}
}
}
} // namespace kafka